 Airborne system and methods for the detection, location and obtaining of images of buried objects an
专利摘要:
Airborne systems and methods for the detection, location and obtaining of images of buried objects and for the characterization of the composition of the subsoil. The systems comprise at least one aerial module (1) with a radar unit (11) that emits and/or captures radar signals and a positioning and guidance system (13) with an accuracy equal to or less than 3 cm, and an earth station (2) with a flight control system (21) and a radar signal processing unit (23) where radar signal processing algorithms (25) are applied. The invention also comprises a method for the detection, localization and obtaining of images of buried objects and a method for the characterization of the composition of the subsoil. Applicable in sectors where it is necessary to perform the detection of buried objects, as for example in civil applications (detection of antipersonnel mines), pipeline inspection or in archeology. (Machine-translation by Google Translate, not legally binding) 公开号:ES2577403A1 申请号:ES201600073 申请日:2016-01-21 公开日:2016-07-14 发明作者:Borja GÓNZALEZ VALDÉS；Yuri ÁLVAREZ LÓPEZ；Ana ARBOLEYA ARBOLEYA；Yolanda RODRÍGUEZ VAQUEIRO；María GARCÍA FERNÁNDEZ；Fernando LAS-HERAS ANDRÉS；Antonio GARCIA PINO 申请人:Universidad de Oviedo；Universidade de Vigo； IPC主号:
专利说明:
DESCRIPTION Airborne systems and methods for the detection, location and imaging of buried objects and the characterization of the subsoil composition. 5 The present invention relates to systems for obtaining images of any buried object of any composition and for characterizing the composition of the subsoil. A system comprises at least one air transmitter and receiver module, an earth station and a communication system between elements. The other system is similar to the previous one, but comprises at least one emitting air module and another receiving air module 10. The invention also relates to radar signal processing methods for obtaining the radar image of the subsoil and of the possible objects buried in the subsoil, including its detection and location, and for characterizing the composition of the subsoil. fifteen The invention is applicable in those sectors in which it is necessary to perform the detection of buried objects, such as in civil applications for mine detection, pipe inspection, archeology or detection of holes or cavities. State of the art 20 The detection of hidden objects in a medium not transparent to visible light using non-invasive techniques (Non Destructive Techniques, NDT) has been of great interest in multiple human activities, such as mining and geology, construction and civil works, and archeology, among others. Non-invasive techniques allow detection, location and, as a final goal, obtaining an image of the hidden object in the surrounding environment, without interacting with the medium or the object itself. The advantages of these systems are fundamentally the economy in resources and time, not being necessary to carry out blind excavations in the area of interest to be able to find the objects. Likewise, it is guaranteed that, in the case of objects of a certain value, they do not suffer damages derived from the excavation. Within the applications described in the previous paragraph, there are scenarios in which the inspection of surfaces is necessary for the detection of objects of potential danger hidden under them, such as weapons or explosives. Under these conditions, the detection and identification must be carried out under safety conditions that guarantee the integrity of both the detection equipment and its operators. Within the aforementioned scenarios, the detection of antipersonnel mines is of special interest, which are responsible each year for 4,000 deaths and mutilations, 40 90% corresponding to civilians, in the approximately 60 countries in which part of their territory is located planted with this type of explosives. It is estimated that there are currently between 59 and 69 million antipersonnel mines buried in the world (International Campaign to ban Landmines. Why Landmines Are Still a Problem [recovered on 2015-11-101. Recovered from the Internet: <http: // www. icbl.org/en- 45 gb / problem / why-landmines-are-still-a-problem.aspx>; and UNICEF Communications Colombia and antipersonnel mines: sowing mines, reaping death, [recovered on 2015-11-10 ] Recovered from the Internet: <http://www.unicef.org/colombia/pdf/ minas.pdf.>). fifty The methods for the detection of antipersonnel mines can be classified into two large groups: - Invasive methods, in which a device capable of detonating the possible mines by contact is used. Low-cost but single-use systems have been devised (the most widespread is MineKafon, (Massoud Hassani, MineKafon [retrieved 20 15-1 1-10]. Recovered from the Internet: <http: //minekafon.blogspot. it />), as well as more robust systems, capable of withstanding several detonations at the cost of increasing the price and complexity of the device (Way Industries AS Slovakia, Bozena Systems [recovered on 2015-11-10 10]. Recovered from the Internet : <http://www.bozena.eu/common/ lile.php file = 44>; and Nicoud, JD, & Habib. MK (1995, August) .The pemex-b autonomous demining robot: perception and navigation strategies Proceedings on 1995 IEEE / RSJ International Conference on Intelligent Robots and Systems 95. 'Human Robot Interaction and Cooperative Robots'. Vol. 1, pp. 419-424. IEEE) .The main drawback of these systems is their impact on the explored terrain, plowing it for exploration. As an advantage, its exploration capacity stands out, since it analyzes 1 square meter in 0.73 seconds. - Non-invasive techniques, in which, from the proper processing of a set of 20 received signals, it is possible to detect the presence of buried objects. Non-invasive techniques can be classified in turn according to the physical phenomenon on which the detection is based (Robledo, L., Carrasco, M., & Mery, D. (2009). A survey of land mine detection technology. International Journal of Remote Sensing. 30 (9), 2399-2410): 25 - Electromagnetic induction. It is based on inducing an electric current in buried metal objects using a transmitter coil. Said current in turn re-radiates an electric field that is detected in a receiving coil. The advantage it presents is its low cost and simplicity of operation. As an inconvenience, 30 has a high false alarm rate, due to the large number of buried metal objects that may be present in a scenario (shrapnel remains, screws ...). - Ground Penetrating Radar (GPR). Considered as one of the best techniques for obtaining subsoil images, it is based on emitting electromagnetic waves capable of penetrating the subsoil, so that from the reflected waves it is possible to perform a radar image and detection of it, identifying possible objects buried. However, it is a very sensitive technique to the composition of the subsoil and to the relief or roughness of the ground, requiring 40 signal processing techniques to eliminate false echoes and other artifacts present in the radar image (clutter). - Nuclear Quadrupole Resonance (NQR). It is based on the observation of the radio frequency signals of certain substances characteristic of explosive materials. These 45 systems provide a high probability of detection, although their complexity is high. - Acoustic and seismic systems. Its principle of operation is similar to the GPR, based on the emission of acoustic waves through the ground. The appropriate processing of the received signal allows the identification of possible buried objects. The false alarm rate is lower than in the case of electromagnetic induction systems. As a disadvantage, the scan time ranges from 2 to 15 minutes per square meter. Other non-invasive detection techniques that are also viable, but less used due to their high operational and technological costs, are: - Image analysis in visible or infrared band, which detects surface patterns that correspond to land where mines have been planted. 10 - Radiography, which has a high detection but is limited to the detection of mines buried near the surface (10 cm or less), in addition to presenting restrictions for the operation with X-rays. - Chemical or biological sensors, to detect chemical components of the explosive material that come to the surface through micro cracks in the mine frame. Regardless of the physical principle, the application of non-invasive techniques for mine detection requires that the detector system keep a safe distance from the possible location of the mine, recommending about 3-5 m of 20 distance, to prevent the weight of the detector system may cause the detonation of the explosive. To achieve this goal there are different possibilities: - Use stand-off radar systems, with which the ground is illuminated with an angle of incidence such that the amount of energy that penetrates is maximized. In this case, the problem arises because, according to Snell's law, the reflected energy will go in the opposite direction to the radar, which decreases the sensitivity of the system. Examples of these systems are described in US 8193965 B2 and US 7479918 B2, where processing capacity is improved using polarimetric techniques. 30 - Use systems capable of illuminating the ground with an incidence perpendicular to the ground (or also called normal incidence). Although the maximum energy cannot be coupled to the ground, this fact is compensated by the possibility of getting closer to it and being able to capture more reflected energy. In this type of systems, the difficulty lies in providing illumination perpendicular to the ground keeping the safety distance of 3-5 m in the vicinity of the radar. Within the alternatives for incidence perpendicular to the ground, there is the possibility of using unmanned autonomous robots of reduced size and weight, which can carry out the detection of mines with a reduced (but not zero) risk of detonation. For example, in the publication of González de Santos, P., García, E., Estremera. J., & Navy. M. A. (2005). DYLEMA: Using walking robots for landmine detection and location. The International Journal of (Systems Science, 36 (9), 545-558 presents a robot equipped with an electromagnetic induction-based detector system and a differential Global Positioning System (GPS) for monitoring and controlling trajectory. Limitation is the scanning speed, which is 5 cm per second. Similarly, in patent document US 751 1654 B1 a GPR-based mine detection system is proposed, in which a robotic vehicle is used to create a radar image of the subsoil, which allows buried objects to be detected and, by consequently, mines. The invention is based on burying a transmitting and receiving antenna in the ground in different positions separated by half wavelength, so that the coherent combination of the serial received in each position allows to create a two-dimensional radar image (in range or range, and in cross-range or direction of movement of the robot). This system, therefore, has the capacity to make 5 radar image with synthetic aperture (SAR). As an inconvenience, the slowness to carry out the inspection process stands out. An alternative to the use of land vehicles and their limitations in terms of land recognition speed (as well as the potential risk of 10 detonation when in contact with the ground) are air vehicles as a detector system. Among them, UAVs (Unmmaned Aerial Vehicles) can be highlighted since the ease of access to small-sized UAVs and their simplicity of maneuverability have triggered their use in multiple disciplines. fifteen In the radar field, in the publication of Marc Lort, Albert Aguasca and Xavier Fabregas (2015). Interferometric and Polarimetric X-band SAR sensor integrated in a small UAV multicopter platform. 2015 URSI National Symposium. Pamplona, September 2015 embarks a polarirnetric radar to make radar image. Polarimetric radars have the advantage that they allow measuring the response of different materials to the 20 electromagnetic waves, being able to use this property not only to obtain the radar image, but also the composition of the materials. Like many UAV systems, it incorporates a GPS receiver with an inertial measurement unit (IMU) to determine the position of the UAV during the flight. The bandwidth used is small, resulting in a resolution in the range of 1.5 m, insufficient resolution to detect objects that may be buried at a lower depth, since it would not be possible to distinguish between reflection in the air-ground interface and Reflection in the buried object. Another SAR radar application embarked on a UAV is described in document 30 Chenchen J. Li. Hao Ling (2015) Synthetic aperture Radar imaging using a small consumer drone. IEEE Antennas and Propagation International Symposium, 2015. Vancouver. The radar, which operates in the 3.1 to 5.3 GHz band, has been mounted on a drone-type UAV. Communication modules for Wi-Fi are used to communicate with an earth station for flight control and radar data reception. The advantage of this radar system plus communications module is that it is compact and light in weight (less than 300 g), so that it can be easily shipped on the UAV. However, the SAR imaging system has not yet been satisfactorily tested in flight for downward-looking SAR illumination due to instability in the UAV's flight path. The UAV 40 incorporates a GPS receiver and inertial sensors, which do not provide sufficient positioning accuracy for a correct consistent combination of serial radar data measured at each UAV flight position. In the field of the detection of explosive objects buried by GPR 45 systems shipped in UAV, already in the Goad document. A., Schorer, D., Sullenberger, J., Yousuf, F., Yu. A., Donohue, G., & Hintz, K. (2008, April). Landmine detection utilizing an unmanned aerial vehicle. Systems and Information Engineering Design Symposium. 2008. SIEDS 2008, IEEE (pp. 231-236), analyzes the capacity of a radar on board a UAV to detect mines, according to different parameters such as the 50 diameter of the mine, the signal to noise ratio of the radar and Flight height But nevertheless, The authors of the study conclude that for the UAVs compared, the system is not realizable because it is necessary to pilot a UAV of considerable size (such as Shadow 200, Shadow 600 and Predator models) at a height less than its operational height ( in order to detect the mines), which can put the UAV at risk due to the danger of collision with the ground. 5 Subsequently, in the document by Rodríguez, J., Castiblanco, C., Mondragon, I., & Colorado, J. (2014, May). Low-cost quadrotor applied for visual detection of landmine-like objects. IEEE 2014 International Conference on Unmanned Aircraft Systems (ICUAS) pp. 83-88, the use of a UAV of reduced dimensions and weight for the detection of 10 mines that are not buried from the analysis of photographs is proposed. As notable features of this system, it is mentioned the fact of using a Wi-Fi connection for communication between the UAV and a sandpaper earth station, as well as having a positioning unit of the UAV formed by different sensors (IMU, magnetometer, altimeter ) that allows the system to trace exploration paths. fifteen In the patent document US 2007/0035304 a detection system is proposed formed by an air unit where the transmitter is shipped and an aerial trailer where the receiver is, thus configuring a bistatic system that works in the frequency range of 80 kHz to 1 MHz. In this case, the system is based on electromagnetic induction, determining the position of the detected objects from the flight time between the transmitted signal and the detected ceo. In a bistatic system, the relative position between the transmitter and the receiver is always the same, so that the ground always lights at the same angle. For certain applications it may provide some more information than a monostatic system 25 (one in which the radar signal is emitted from the same point it is received), but it is more limited than a multistatic system, where the separation between transmitter and receiver to have more spatial diversity. Polarimetric techniques have also been applied in on-board UAV systems 30 for GPR applications, as described in US 7528762 B2, where the system, designed to work in the 1 MHz to 1 GHz band, employs a technique of Signal processing based on polarimetry that eliminates the air-ground clutter. This technique is based on selecting, in the first place, the appropriate frequency and angle of incidence to maximize soil penetration taking into account the characteristics of the soil and the depth of penetration. Next, the dispersed field is acquired for the two polarizations, typically orthogonal to each other, and the coherent difference between the two signals is calculated. The echoes that are not canceled correspond to reflections in buried objects, because the subsoil changes the polarization of the field differently from the object to be detected (since in general the subsoil and the object will have different composition). With respect to the hardware, an on-board system is contemplated, placing the antennas on the blades of a helicopter. The main limitation of this processing technique is that it is only suitable for stand-off systems (the radar is at a distance of several meters from the surface to be scanned). Four. Five The invention described in patent document US 2014/0062754 A1 is based on a GPR system embarked on a UAV, which is able to position itself autonomously following a previously defined path (for example, zigzag), using the information provided by a system Differential GPS In addition, in case of loss of the GPS signal 50, the mentioned document contemplates that it is possible to use the inertial sensor information to maintain the trajectory, such as magnetometers and gyroscopes. A flight height of 66 to 330 cm is defined, with a positioning accuracy of 16.5 cm. The working frequency range is 4 to 6 GHz. The radar signal is processed in the system on board the UAV, the resulting radar image being sent to an earth station via a wireless link. 5 This system has a scanning speed of 24 seconds per square meter (25 square meters in 10 minutes). In addition to the mentioned characteristics, this system also incorporates countermeasures to deactivate the mine, landing the UAV on the area where the mine has been detected and using chemical elements capable of canceling the explosive. 10 An invention similar to the above is described in US patent document 2014/0062758 A1. In this case, the system is able to identify irregular floor patterns with an optical camera and a thermal camera. Once detected, a GPR radar is used to detect possible buried objects. If positive, it is capable of applying the countermeasures mentioned in the previous invention to cancel the explosive capacity. In addition, it contemplates the use of a low resolution radar to detect buried objects. If the detection is positive, it is switched to a high resolution radar for better identification of the buried object. twenty In the inventions listed above where a GPR radar embarked on a UAV is used for mine detection (US 7528762 B2, US 2014/0062754 A1. US 2014/0062758 A1) there is no possibility of obtaining a radar image based on synthetic aperture, that is to say, coherently combining the radar measurements taken in the different positions of the UAV flight. This is because the accuracy of positioning is 16.5 cm (at best), 6.6 times greater than the working wavelength of the radar system (6 GHz at the highest frequency). In order to use synthetic opening techniques, it is necessary that the data acquisition positions be separated half a wavelength at the working frequency. The point-to-point representation of the radar signal processed in range or range implies a loss of spatial resolution (cross-range) with respect to SAR processing (fig. 1). The possibility of using a UAV assembly is described in US 6653970 B1. In it, a UAV emits a signal that is received in one or several UAVs, the position of all of them being known. The system is used for the detection of targets in high multipath environments (such as mountainous areas or with numerous constructions where the transmitted signal undergoes multiple reflections), using delay measurement as a method to detect target positions. The use of multistatic systems (that is, the transmitter and the receiver are in different positions from each other) allows to increase the information collected from scenario 40 under study by having more lighting angles (Álvarez, Y., Rodríguez-Vaqueiro, Y. , González-Valdés, B., Mantzavinos, S .. Rappaport. CM, Las-Heras, F., & Martinez-Lorenzo, JA (2014). Fourier-based imaging for multistatic radar systems. Microwave Theory and Techniques, IEEE Transactions on, 62 (8), 1798-1810); Gonzalez-Valdes, B., Rappaport. C., Lorenzo, M., Jose, A., Álvarez, Y., & Las-Heras. F. (2015, July). Imaging 45 effectiveness of multistatic radar for human body imaging. Antennas and Propagation & USNC / URSI National Radio Science Meeting, 2015 IEEE International Symposium on (pp. 681-682). IEEE.). Although the invention described in patent document US 6653970 B 1 indicates that SAR processing is used, the measurement of the position of the transmitting UAV and the receivers is based on GPS receivers, whereby the accuracy obtained in the position no. may be less than 1 m (which is the accuracy of the GPS in use civil in the best operating conditions), which makes the detection of targets inaccurate, with position errors that in many applications exceed the threshold of the admissible. Although most of the mines are metallic, easy to detect by most 5 of the systems, plastic explosives have recently been developed, whose low dielectric contrast with respect to the subsoil in which they are buried makes their detection difficult. In this sense, a possible solution is the determination of the composition of the subsoil so that it can be used as a contrast with respect to the material to be detected. 10 Thus, for example, the invention set forth in US 8849523 B1 describes a system capable of determining the composition of the subsoil using a GPR radar, although it is on board a tractor-type land vehicle used for sowing seeds, which greatly penalizes the speed of 15 analyzes. On the other hand, this patent does not specify what the method of determining the composition of the subsoil consists of, therefore the precision parameters are unknown, if it estimates both permittivity and conductivity, or what processing algorithm is used. twenty There are various techniques to determine the constitutive parameters of the subsoil. For example, in the publication of Ramirez, A., Daily, W., LaBrecque, D., Owen, E., & Chesnut, D. Monitoring an underground steam injection process using electrical resistance tomography, Water Resources Research. Vol. 29, No. 1, pp. 73-87, 1993 and in Zhou, QY, Shimada, J., & Sato, A., Three-dimensional spatial and temporal 25 monitoring of soil water content using electrical resistivity tomography, Water Resources Research, Vol. 37, No 2, pp. 273-285, 2001 low-frequency electrical resistivity tomography (ERT) and electromagnetic induction (EMI) are used to determine the water content of the subsoil. In the publication of Hendrickx, J. M. H., Borchers, B., Corwin, D. L., Lesch, S. M., Hilgendorf, A. C., & Schlue, J., Inversion of soil conductivity profiles from 30 electromagnetic induction measurements, Soil Science Society of America Journal. Vol. 66. No. 3, pp. 673-685. 2002 these techniques are also used to determine the conductivity of the subsoil. Although these techniques allow characterization of the subsoil and detection of possible buried objects, the nature of the signals used does not allow obtaining high-resolution images of the subsoil that facilitate the identification of, among others, the buried objects that are trying to be located. With respect to the use of GPR systems, in the document of Busch, S., Van der Kruk. J., & Vereecken, H., Improved characterization of fine-texture soils using on-ground GPR full-waveform inversion. IEEE Transactions on Geoscience and Remote Sensing, Vol. 52, 40 No. 7, pp. 3947-3958, July 20 14 an electromagnetic model that characterizes the subsoil is proposed, considering a cost function that minimizes the difference between the measured electromagnetic field and the electromagnetic field radiated by the electromagnetic model that characterizes the subsoil. When said difference is minimal, it is considered that the constituent parameters of the subsoil have been found. The limitation of this method is the establishment of an electromagnetic model that increases the complexity of the system. Especially critical is the fact that it is based on global and local optimization techniques, which are quite sensitive to uncertainties in the measurements, and may lead to an erroneous estimation of the constituent parameters of the subsoil. fifty In the publication of C. R., Morton Jr, K. D., Collins. L. M., & Torrione. P. A., Analysis of linear prediction for soil characterization in GPR data for countermine Applications, Sensing and Imaging, Vol. 15. No. 1. pp. 1-20, 2014 mentions the importance of the correct characterization of the subsoil in applications for GPR and, specifically, applied to the detection of mines: 5 "Although the phenomenology behind GPR is essentially the same as in airborne or ground radars, transmitting and receiving signals that propagate through the subsoil generates numerous challenges of intrinsic signal processing to GPR systems. Unlike conventional radars, The propagation channel in a GPR is heterogeneous in nature - the presence of clutter in the subsoil is quite common, and differences in soil density and humidity can affect the dielectric properties that determine the propagation speed and intensity of the white radar signature. GPR signals also interact with the ground surface (as well as other subsoil interfaces, such as the bed of a road or a road), which is generally rough and contributes to additional clutter in general. " (Trad. a.). The estimation of the constitutive parameters is typically performed using linear prediction (LP) models based on autoregressive processes (AR) that use signal patterns known as a database (or training being) to subsequently perform the classification of the measured signal. , associating it with a certain type of subsoil. Although the precision obtained in the reconstruction of the subsoil parameters is high even in the case of highly non-homogeneous soils, the main drawback is the need to train the characterization algorithm, which requires having a large number of training measures performed under real conditions that cover a multitude of different cases, in addition to restricting the algorithm for a specific GPR system (applying the algorithm in another GPR system would require a new database). Description of the invention 30 The present invention relates to systems for obtaining images of any buried object of any composition and for characterizing the composition of the soil and subsoil, comprising one or more aerial modules, an earth station and a communication system between elements. The invention also relates to the methods of signal processing radar to obtain the radar image of the subsoil and the possible objects buried in the subsoil, including its detection and location, and to characterize the composition of the subsoil. For the purposes of this invention and its description, soil refers to the surface that separates the air from the subsoil, and subsoil to the material medium where the potential objects to be located are buried. The invention preferably relates to soil and subsoil, such as a terrestrial surface and the material medium beneath it, although it could also be applied more generically to other types of material surfaces and media, such as, for example, a water surface. and the material medium where the potential objects to be located are submerged. For the purposes of this invention and its description, operator refers to the person in charge of the supervision of the different systems and methods that make up the invention, as well as interacting with the different processes that require person-machine communication. For the purposes of this invention and its description, the area under study refers to the soil and subsoil that is to be inspected, in search of possible buried objects. An aspect of the present invention is an airborne system for detection, location and imaging of buried objects. From now on, this aspect of the invention can be referred to as a "monostatic system". The monostatic system comprises: - At least one air module that in turn comprises a radar unit that emits and captures radar signals directed and reflected on the ground, a positioning and guided system of the air module, and an air control unit that collects information from the unit radar and positioning and guidance system, controls flight parameters of the aerial module and exchanges information with an earth station. - An earth station which in turn comprises a flight control system of the air module, a radar signal processing unit received from the radar unit that processes the radar signals by means of a set of radar signal processing algorithms, and a computer application for the representation of the radar image of the subsoil obtained from the radar signal processing unit. twenty - A means of communication to emit and receive wireless signals between the air module and the earth station. The positioning and guidance system of the aerial module comprises a global positioning system, a positioning system based on inertial sensors, a positioning system based on real-time satellite kinetic navigation or RTK (from Real Time Kinematik), which exchanges information with a real-time satellite kinetic navigation base station located in the earth station, and a positioning system based on photogrammetry. The positioning and guidance system sends information to the aerial control unit, providing the precise three-dimensional location of the aerial module and the georeferencing of the data obtained with the radar unit, with an accuracy of value equal to or less than three centimeters. The detection, location and imaging of buried objects is made from the information that the air module exchanges with the earth station, where 35 is processed in the radar signal processing unit through a set of processing algorithms of the radar signal One of these algorithms is a SAR processing algorithm for obtaining the radar image and another is a clutter elimination algorithm of the radar image. The aforementioned algorithms require precise three-dimensional localization, with a value equal to or less than half a wavelength for the maximum 40 working frequency, of the aerial module and the georeferencing of the data obtained with the radar unit in order to carry out the coherent processing ( that is, using amplitude and phase information of the measured radar signal) of the measured radar signal in different positions, thus creating a synthetic radar aperture. One way to treat the digitized radar signals received by a SAR processing algorithm and a clutter elimination algorithm is to store them in matrix form and associate them with a coordinate matrix, as will be explained later in this description. Another aspect of the present invention is another airborne system for detection, location and imaging of buried objects. From now on it will It may refer to this other aspect of the invention as a "multi-static system". The multistatic system comprises: - At least one air module, which is an air transmitter module, which in turn comprises a radar unit that emits radar signals, a positioning and guidance system of the air transmitter module, and an air control unit that collects information from the radar unit and positioning and guidance system, controls flight parameters of the emitting air module and exchanges information with an earth station. - At least one air module, which is a receiving air module, which in turn comprises a radar unit that captures the radar signal, a positioning and guidance system of the receiving air module, and an air control unit that collects information from The radar unit and the positioning and guidance system control flight parameters of the receiving air module and exchange information with an earth station. fifteen - An earth station which in turn comprises a flight control system of the sending air module and the receiving air module, a radar signal processing unit received from the radar unit that processes the radar signals by means of a set of processing algorithms of radar signal, and a computer application for the representation of the radar image of the subsoil obtained from the radar signal processing unit. - Communication means for sending and receiving wireless signals between the sending air module and the earth station, between the receiving air module and the earth station, and between the sending air module and the receiving air module. 25 The positioning and guidance system of the sending air module and the receiving air module comprises a global positioning system, a positioning system based on inertial sensors, a positioning system based on real-time satellite kinetic navigation or RTK, which exchanges information with 30 a real-time satellite kinetic navigation base station located in the earth station, and a positioning system based on photogrammetry. The positioning and guidance system sends information to the air control unit providing the precise three-dimensional location of the sending air module and the receiving air module and the georeferencing of the data obtained with the radar unit with an accuracy of value equal to or less than three centimeters. A radar signal processing algorithm of the radar signal processing unit is a SAR processing algorithm for obtaining the radar image and another is a clutter elimination algorithm of the radar image. 40 In a preferred embodiment of either of the two systems, monostatic or multistatic, the aerial module is an unmanned aerial vehicle. In a more preferred embodiment, the unmanned aerial vehicle is of the multi-rotor type. In another preferred embodiment of the monostatic system, the communication means 45 comprise a two-way and real-time communication system between the air module and the earth station, such as two low frequency transceivers, one located at the earth station and the other in the aerial module. In another preferred embodiment of the multi-static system, the communication means 50 comprises a two-way and real-time communication system between the module air transmitter and earth station, a two-way and real-time communication system between the receiving air module and the earth station, and a real-time two-way radar communication system between the radar unit on board the emitting air module and the unit radar on board the aerial receiver module. 5 In another more preferred embodiment of the communication system between the air module and the earth station of the monostatic system or of the radar communication system between the radar units of the emitting and receiving air vehicles of the multistatic system, said systems comprise one or more communication modules 3G / 4G or one or more low frequency transceivers or an IEEE 802.11 (Wi-Fi) interface or one or more 10 Zigbee modules or one or more Bluetooth modules, or a combination of any of the above communication media. An example of this embodiment is a communication system consisting of two Zigbee or Bluetooth modules, one located in the earth station and the other in an air module. Another example of this embodiment is a communication system formed by two 3G / 4G communication modules, one located in the earth station and the other in an air module. Another example of this embodiment is a communication system consisting of two IEEE 802.11 (Wi-Fi) communication interfaces, one located in the earth station and the other in an aerial module. Another example of this embodiment is a system formed by two low frequency transceivers, one located in the earth station and the other in an air module. Another example of this embodiment is a radar communication system between the two radar modules embarked on the two aerial modules, formed by two low frequency transceivers, each embarked on an aerial module. In a specific embodiment of the monostatic system, the radar unit of the air module 25 comprises: - A transmitting antenna and a receiving antenna. - A radar module for the generation of an electromagnetic signal in a 30 frequency band whose frequency is greater than or equal to 5 GHz, and for the reception of the dispersed electromagnetic signal. In a specific embodiment of the multistatic system, the radar unit of the emitting air module comprises: - A transmitting antenna. - A radar module for the generation of an electromagnetic signal in a frequency band whose frequency is greater than or equal to 5 GHz. 40 In another specific embodiment of the multistatic system, the radar unit of the receiving aerial module comprises: - A receiving antenna. Four. Five - A radar module for receiving the dispersed electromagnetic signal. In a preferred embodiment, the transmitting and receiving antennas will have circular polarization, the circular polarization of the transmitting antenna being orthogonal to the circular polarization 50 of the receiving antenna. In an even more preferred embodiment, the antennas The transmitter and receiver are helical type antennas, with an S11 parameter lower than -15 dB in the frequency band in which the radar module operates, and a gain greater than 10 dB. In another preferred embodiment, the receiving antenna is formed by an array of two elements, the circular polarization of each element being orthogonal to the circular polarization of the other element. The element from which it is desired to receive the radar signal 5 is selected by a switch or switch that connects the element to the radar unit. The switching between the two elements allows to obtain polarimetric information. In another specific embodiment of the monostatic system or the multistatic system, the flight control system of the module or of the aerial modules comprises a manual flight control system 10 and a system for the generation of trajectories and automatic flight control. Through these systems, it is possible to plan in advance the exploration of the area of interest, the predetermination of the movement of the air module or the relative position between several air modules, it is also possible to implement an adaptive system that, in real time, determines efficient trajectories according to to a series of 15 contour parameters (orography, boundaries, atmospheric conditions, etc.). Through the manual flight control system, an operator can monitor the development of the exploration and at any time take control to make corrections or avoid accidents. twenty In this way, the scanning path followed by the aerial module to explore a specific area under study can be introduced by means of the system for the generation of trajectories and automatic flight control through, for example, a geo-referenced coordinate file. Once introduced, the operator of the invention may instruct the system to begin scanning. The manual flight control system 25 will allow the operator of the invention to immediately take control of the flight of the aerial module in case of danger of collision, presence of strong wind that alters the automatic path or the like, landing it in a safe place. In another specific embodiment of the monostatic system or the multistatic system, the SAR processing algorithm for obtaining the radar image employs polarimetric information. In a more specific embodiment, the polarimetric information is obtained from the acquisition of the radar signal for two orthogonal polarizations of the dispersed electric field. In this way it is possible to increase the diversity of information, reconstructing a three-dimensional radar image for each polarization. These 35 three-dimensional images are combined, allowing a better elimination of false radar and clutter echoes, since typically the ground, subsoil and possible buried objects have different types of responses for different polarizations. In another specific embodiment of the monostatic system or the multistatic system, the set of serial radar processing algorithms also comprises an algorithm to correct the defocusing of the radar image due to the uncertainty associated with the positioning and guidance system of the aerial module and a algorithm for the detection of buried objects. Four. Five In another specific embodiment of the monostatic system or multistatic system with a set of radar signal processing algorithms that are a SAR processing algorithm for obtaining the radar image and a clutter elimination algorithm of the radar image, it also comprises a algorithm for the characterization of the subsoil composition. fifty In a more specific embodiment of the above, the algorithm for the characterization of the subsoil composition performs the estimation of the permittivity of the subsoil from the determination of the distance between the echo in the ground and the echo in a metallic object calibration, observable both in the radar image. In another more specific embodiment, the algorithm for the characterization of the subsoil composition carries out the estimation of the permittivity of the subsoil from the measurement of the amplitude difference between the echo in the ground and the echo in a metallic object Calibration In another more specific embodiment, the radar image clutter removal algorithm is based on an iterative calculation process in which the effect of the ground on the radar image is identified based on the altitude of the aerial module and the estimation of the Composition 10 of the subsoil that provides the algorithm for the characterization of the subsoil composition and subsequently removed from the image using a mask-based algorithm and a SAR processing algorithm for obtaining the radar image. For the purposes of this invention and its description, echo is the reflection observed in the radar image (or in a radar signal) when there is a change in the propagation medium. In this way, echo in the ground is the reflection of the signal when it hits the ground. Part of the energy is reflected (the echo) and part of the energy is transmitted to the subsoil. In the echo in a metallic calibration object, all energy is reflected because it is a metallic object that does not allow an electromagnetic wave to pass through it. twenty In a preferred embodiment of the monostatic system, the aerial module emits and captures radar signals establishing its position at different heights relative to the ground. In a preferred embodiment of the multistatic system, the sending air module emits 25 radar signals establishing its position at different heights relative to the ground and the receiving air module captures radar signals establishing its position at different heights relative to the ground. In a more preferred embodiment of the monostatic system or the multistatic system 30 above in which radar signals are emitted and / or captured by establishing the position at different heights relative to the ground, the radar image created with the radar signals obtained at different heights are combined to detect, locate and obtain the image of the ground and the objects buried in the subsoil. 35 In another more preferred embodiment of the monostatic system or the multistatic system in which radar signals are emitted and / or captured by establishing the position at different heights relative to the ground, the SAR processing algorithm for obtaining the radar image is based on the sum coherent radar signal measured in two or more positions of the aerial module, provided that the separation between two consecutive positions is equal to or less than 40 half wavelength at the highest working frequency. Another object of the present invention is a method for the detection, location, and imaging of buried objects comprising the following steps: Four. Five a) Issue a radar signal generated by a radar unit to the ground that you want to inspect. b) Capture the radar signal reflected in the ground, subsoil and possible buried objects through a radar unit and determine the precise three-dimensional location of the aerial module 50 with an accuracy of value equal to or less than three centimeters. c) Send the radar signal and the precise three-dimensional location of the air module to the earth station using the communication system. d) Process the radar signal in the radar signal processing unit to obtain a three-dimensional image of the subsoil and detect and locate possible buried objects 5 through a set of radar signal processing algorithms that comprise a SAR processing algorithm for obtaining the radar image and a clutter elimination algorithm of the radar image. In a preferred embodiment of the method, the radar signal generated by the radar unit is emitted from the emitting air module, and the reception of the radar signal reflected in the ground, subsoil and possible buried objects is performed in the radar unit embarked on the aerial receiver module. The emission and reception are synchronized by a radar communication system on board each air module. fifteen In a preferred embodiment of the method in which one or more aerial modules are used, the radar unit also processes the radar signal received in step b) to convert it to a digital sequence, and in step d) the signal processing unit Radar processes the serialized radar radar. In this way, the radar signal converted to digital sequence is sent to the earth station where the radar signal processing unit 20 processes the digitized radar signal using the set of radar signal processing algorithms. In another preferred embodiment of the method in which one or more aerial modules are used, the radar signal is a train of electromagnetic pulses. 25 To carry out the detection and location of buried objects, the procedure described in the method [steps a) to d)] is repeated for each of the positions of the scanning path that describes the aerial module or modules to explore a certain area under study, which allows obtaining an image or an image composition of the area of interest. In another preferred embodiment of the method in which one or more aerial modules are used, the position of the aerial module is also varied and steps a), b) and c) are repeated prior to stage d). In a more preferred embodiment, the radar image created with the radar signals obtained at different heights is combined to detect, locate and obtain the image of the ground and the objects buried in the subsoil. In another preferred embodiment of the method in which one or more aerial modules are used or the method in which one or more aerial modules are used and their position is varied, the SAR processing algorithm for obtaining the radar image is based on the coherent sum of the radar signal measured in two or more positions of the aerial module, provided that the separation between two consecutive positions is equal to or less than half a wavelength at the highest working frequency. Four. Five One way to treat the digitized radar signals received for each position by storing them in a matrix, where each row of the matrix corresponds to a position. The coordinates of each position of the air module are stored in a coordinate matrix. Using the information of the positions of the aerial module, and known the size of the subsoil that you want to inspect, a 50 transformation matrix is constructed that relates the points of the subsoil with the positions of the module aerial. SAR processing performs mathematical operations with the transformation matrix and the matrix of the digitized radar signals to calculate the reflectivity of the soil and subsoil. This reflectivity is processed using the clutter removal algorithm to highlight the possible presence of buried objects and eliminate soil reflection. The procedure for eliminating the clutter is iterative: i) known radar signals and the positions where they have been measured, SAR processing is applied to calculate the reflectivity in the area under study; ii) from the reflectivity in the area under study it is possible to identify the reflection of the signal! ground radar; ii) a mask is applied that encompasses the region of the area under study corresponding to the reflection of the radar signal on the ground; iii) the radar signal that reflects the masked region is calculated; iv) a new array of radar signals equal to the initial radar signal array is created minus the radar signal that reflects the masked region; and v) SAR processing is applied to the matrix resulting from the subtraction, obtaining the reflectivity in the area under study. Steps i) to v) are repeated a certain number of times, so that in each iteration the contribution due to reflection in the ground (masked region) is attenuated. 15 Finally, the processed reflectivity is shown as a three-dimensional image of the subsoil in the computer application developed for the representation of the radar image of the subsoil. For the purposes of this invention and its description, reflectivity is a dimensionless magnitude relative to the intensity of the ratio between the reflected radar signal and the incident radar signal at each point in space. In another preferred embodiment of the method in which one or more aerial modules are used or the method in which one or more aerial modules are used and their position is varied, the SAR processing algorithm for obtaining the radar image employs information polarimetric, obtained from the acquisition of the radar signal for two orthogonal polarizations of the dispersed electric field. In another preferred embodiment of the method in which one or more aerial modules 30 is used or the method in which one or more aerial modules are used and their position is varied, in step d) the radar signal is processed in the processing unit of radar signals by means of a set of serial radar processing algorithms that also comprise an algorithm to correct the blurring of the radar image, and an algorithm for the detection of buried objects. Thus, the SAR processing algorithm and the clutter elimination algorithm are combined with an algorithm to correct the blurring of the radar image due to the uncertainty associated with the positioning and guidance system. Wind, changes in air pressure or similar situations may introduce small changes in the path to be followed by the air module. To carry it out, the method called Phase Gradient Autofocus 40 (PGA) can be used, consisting of identifying characteristic points in different radar images, and correcting the blur by applying poisoning and offset operations. On the other hand, the three-dimensional image of the subsoil is processed by an algorithm for the detection of buried objects. This algorithm processes the three-dimensional image 45 of the subsoil for clusters of points with high reflectivity, which can correspond to buried objects. The algorithm analyzes the shape of the area or volume with high reflectivity and, based on training patterns stored in a database, decides whether it corresponds to a potential buried object or not. These training patterns are obtained from photographs of different types of 50 buried objects (antipersonnel mines, archaeological remains, pipes, etc.) and can be calculated before scanning the area under study. In a specific embodiment of the method in which one or several aerial modules are used or the method in which one or more aerial modules are used and their position is varied, the SAR processing algorithm and the clutter elimination algorithm are combined with an algorithm for the characterization of the subsoil composition. For this, prior to stage a), the method also includes the following stages: e) Bury a metallic calibration object in the subsoil. 10 f) Issue a radar signal generated by a radar unit to the ground where the metallic calibration object is buried. g) Capture the radar signal reflected in the ground, subsoil and in the metallic object of calibration through a radar unit, and determine the precise three-dimensional location of the aerial module with an accuracy of value equal to or less than three centimeters. h) Send the radar signal and the precise three-dimensional location of the sending air module and the receiving air module to the earth station using the communication system. twenty i) Process the radar signal in the radar signal processing unit to characterize the composition of the subsoil by means of an algorithm for the characterization of the subsoil composition in which the echo in the ground and the echo in a metallic calibration object is considered . 25 In a more specific embodiment of the above, steps e), f), g), h) and i) to characterize the composition of the subsoil are executed only once, prior to stage a). In this way, the metallic calibration object is buried in one place and the ground effect is determined only once. After this, the exploration of the area of interest begins in order to locate and identify the possible buried objects, but with the information of the soil composition already known. In another more specific embodiment of the method, the algorithm for the characterization of the subsoil composition carries out the estimation of the permittivity of the subsoil from the determination of the distance between the echo in the ground and the echo in a metallic object Calibration In another more specific embodiment of the method, the algorithm for the characterization of the subsoil composition carries out the estimation of the permittivity of the subsoil from the measurement of the amplitude difference between the echo in the soil and the echo in a metallic object of calibration. The algorithm for the characterization of the subsoil composition allows to calculate the permittivity value of the subsoil and, consequently, the propagation speed of the radar signal in the subsoil, so that the transformation matrix used in SAR processing can be build taking into account the speed of propagation of the signal both in the air environment and in the subsoil. In another more specific embodiment of the method in which the composition of the subsoil is previously characterized by an algorithm for the characterization of the Composition of the subsoil, the algorithm of elimination of the radar image clutter is based on an iterative calculation process in which the effect of the soil on the radar image is identified based on the altitude of the aerial module and the estimation of the composition of the subsoil that provides the algorithm for the characterization of the subsoil composition. Subsequently, the clutter is removed from the image using a mask-based algorithm 5 and a SAR processing algorithm to obtain the radar image. Another object of the present invention is a method for characterizing the composition of the soil and subsoil comprising the following steps: a) Bury a metallic calibration object in the subsoil. b) Issue a radar signal generated by a radar unit to the ground where the metallic calibration object is buried. fifteen c) Capture the radar signal reflected on the ground, subsoil and on the metallic calibration object through a radar unit, and determine the precise three-dimensional location of the aerial module with an accuracy of value equal to or less than three centimeters. twenty d) Send the radar signal and the precise three-dimensional location of the air module to the earth station using the communication system. e) Process the radar signal in the radar signal processing unit to characterize the composition of the soil and the subsoil by means of an algorithm for the characterization of the composition of the subsoil in which the echo in the ground and the echo in a metallic object of calibration. In a preferred embodiment, the method for characterizing the composition of the subsoil is performed before proceeding with the method for the detection, location and obtaining of 30 images of buried objects in which the scan of the area under study is performed, for the purpose to obtain the permittivity value of the subsoil that allows to calculate the propagation speed of the radar signal in the subsoil. In a specific embodiment, the emission in step b) is carried out from an emitting air module 35 with a radar unit that transmits a radar signal, and the reception of step e) is carried out by an air receiver module with another unit of radar that captures the radar signal, located in two different positions. In this embodiment, the transmission and reception are synchronized by a radar communication system. 40 In a preferred embodiment of the method in which one or two aerial modules are used, the algorithm for the characterization of the subsoil composition carries out the estimation of the subsoil permittivity from the determination of the distance between the echo in the ground and echo in a metallic calibration object. Four. Five In another preferred embodiment of the method in which one or two aerial modules are used, the algorithm for the characterization of the subsoil composition performs the estimation of the permittivity of the subsoil by means of an algorithm that analyzes the difference in amplitude between the echo in the floor and the echo in a metallic calibration object. fifty The invention provides systems for detecting, locating and obtaining a three-dimensional image of the subsoil as well as possible elements buried therein. The systems of the invention allow to obtain images with a higher resolution with respect to the known systems. The ability to obtain images with 5 centimeter precision in three dimensions is achieved thanks to the systems providing the precise three-dimensional location of the aerial module or modules and the georeferencing of the data obtained with the radar unit. In order to use synthetic opening radar or SAR (Synthetic Aperture Radar) processing techniques, it is necessary that the data acquisition positions be separated by a maximum half length of 10 wave at the working frequency which, considering the working frequencies of the Radar system (5 GHz at the highest frequency) is a design limitation for traditional systems that the systems of the invention overcome in an innovative way. Considering even a scenario in which the three-dimensional location range of the 15 module or aerial modules is 3 cm, the systems can work in a frequency band whose maximum frequency is 5 GHz (medium wavelength positioning accuracy, which at 5 GHz are 3 cm). Even with this working frequency, superior object detection is achieved, efficiently maintaining a compromise between resolution in range or depth (with a maximum bandwidth of 5 GHz there is a resolution of 3 cm in depth) and the capacity of the electromagnetic wave to penetrate the subsoil (penetration depth decreases with increasing frequency, since there is more attenuation). Thanks to its configuration, the aerial module or modules of the present invention are capable of positioning with an accuracy of value equal to or less than three centimeters which, at the working frequencies considered, allows the application of SAR processing techniques through the coherent combination of the radar signal measurements taken in different positions. 30 The SAR processing allows to create, as its name implies, a synthetic aperture that increases the resolution in cross-range (direction of movement parallel to the ground) of the radar system. On the contrary, the point-to-point representation of the radar signal processed only in range or range implies a loss of resolution in cross-range with respect to SAR processing (Fig. 1). 35 The possibility of obtaining three-dimensional images with higher resolution than other GPR systems, allows to detect and locate smaller objects even when they are buried at shallow depth, being possible even in these cases to distinguish between reflection in the air-ground interface (echo in the ground) and reflection in the buried object 40 (echo in the buried object). The fact of using any of the systems of the invention, with at least one aerial module, allows the exploration of the area under study in a fast enough time: up to 25 square meters in 10 seconds, as well as other systems of on-board exploration. in UAV. This time is significantly less than that of detection systems on autonomous robots that move on the ground (half a meter in 10 seconds). One of the embodiments of the invention contemplates the use of a system formed by two two air modules, such as two UAVs: in one the module is shipped radar transmitter, and on the other the radar receiver module. This configuration, called multistatic, allows to increase the spatial diversity of the serial radar, getting to illuminate the ground and the subsoil from different angles, thus increasing the available information regarding a monostatic configuration, which is used by most systems shipped for photogrammetry, SAR radar and GPR. 5 Having more information allows you to increase the detection capacity, making it possible to solve false echoes. One of the radar signal processing algorithms of the invention is a clutter elimination algorithm of the radar image, which is used in combination with a SAR processing algorithm. The clutter elimination algorithm allows to eliminate that part of the received radar signal that is due to the reflection in the ground and that partially masks the echoes of the objects buried in the subsoil. The combination of the SAR processing and the clutter elimination algorithm therefore allows to increase the contrast between the noise or clutter and the objects present in the image of the reconstructed subsoil, increasing the detection capacity of the invention. In a preferred embodiment of the invention, the set of the radar signal processing algorithms further comprise an algorithm for correcting the blurring of the radar image due to the uncertainty associated with the positioning and guidance system 20 of the aerial module, and an algorithm for Buried object detection. The correction of the blurring of the radar image increases the sharpness, making it easier for the algorithm for the detection of buried objects to increase their probability of detection and reduce that of false alarm or false detection. 25 In a preferred embodiment of the invention, the radar signal is received through two antennas with orthogonal polarizations, to have polarization diversity or polarimetric information. One of the embodiments of the radar signal processing method allows to obtain a clear image of the subsoil and the possible elements buried in it, thanks to the use of the SAR processing algorithm combined with an algorithm for clutter removal and an algorithm to correct the blurring of the radar image. This unfocused is due to the oscillations of the UAV (caused by wind, small changes in air pressure ...). 35 In an operating mode of any of the systems of the invention, the aerial module emits and / or captures radar signals establishing its position at different heights relative to the ground. In this way, there is a greater diversity of spatial information, advantageous in the application of the algorithm to correct the blurring of the radar image, 40 by having a greater amount of three-dimensional images of the subsoil taken in different positions, making it easier to calculate the displacement and lag necessary to compensate for blurring. A method of the present invention consists of a process for characterizing the composition of the subsoil, using any of the systems of the invention. In this way, the same system can be used simultaneously to characterize a terrain or to detect elements buried in it. The same system can also be used only to perform a characterization of a subsoil, for example for agricultural applications. This feature gives the system a functional spectrum 50 higher than other known systems. On the other hand, the determination of The composition of the subsoil, and specifically the permittivity value, is used in post-processing of the radar signal to correctly recover the position of the buried objects in the subsoil. Thus, knowing the permittivity value, it is possible to calculate the propagation speed of the radar signal in the subsoil which, together with other variables such as the propagation speed in other transition means, make the determination of the location of buried objects be precise The correct determination of the position of the buried objects in the subsoil also helps to better eliminate the clutter. The method of characterization of the subsoil composition is not linked to a specific GPR system 10, that is, that the subsoil characterization method is used for any GPR system, either embarked on an aerial vehicle, or for a forward looking GPR, etc. Even if in the GPR it is necessary to change some characteristic of it (radar module, antennas ...) it is not necessary to recalibrate the method of subsoil characterization, since the processing algorithm is independent of the system. fifteen The method of characterizing the subsoil composition is simple and quick to implement by any operator of the invention. It only requires burying in the subsoil to characterize a metallic reference object, place the aerial module on top of it and launch a measurement (a set of measurements is not necessary). The subsoil characterization algorithm automatically performs the determination of the constituent parameters, which will be used for the subsequent processing of the radar measurements. The method of characterization of the subsoil composition is based on the measurement of 25 distances between reflections on known objects or surfaces, avoiding both the use of electromagnetic models that characterize the subsoil and the use of minimization techniques or resolution of inverse electromagnetic problems, that increase the computational complexity of the system. 30 The invention is applicable in those sectors in which it is necessary to perform the detection of buried objects, such as in civil applications for mine detection, pipe inspection, archeology and detection of holes or cavities. Description of the figures 35 Fig. 1 corresponds to the State of the Art (E.T.) and represents a comparison between calculated radar images. In the graphic on the left, the image is obtained using a SAR processing algorithm to obtain a radar image. In the graphic on the right, the image is obtained directly by representing the radar signal measured at every 40 points (migrating the time axis to the distance axis). The magnitude represented in each graph corresponds to the radar reflectivity normalized in units of decibels, whose scale is represented in the rule on the right with values from -20 to 0. The units of the 'x' e 'y' axes of the graphs they come in meters [m]. The results represented correspond to two circular metal objects located at (x; y) = (0.1; -0, 15) m, 45 y (x; y) = (-0.1; 0.18) m, buried 12 and 8 cm below the surface in a container of dimensions 0.35 x 0.45 x 0.2 m, filled with sand. The GPR radar scanned in a plane of 1 m x 1 m at a height of 50 cm above the sand surface. As can be seen, in the graph on the left, where the SAR processing algorithm has been used, the two circulated metal objects 50 buried in the sand, corresponding to the maximum reflectivity values, can be clearly distinguished represented. On the contrary, in the graph on the right, where the radar signal measured at each point has been represented, it is not possible to identify these objects. Fig. 2 shows a general scheme of the monostatic system in which the elements that compose it are identified. In the figure you can see an aerial module (1) formed by a radar unit (11), a positioning and guidance system (13) of the aerial module (1) and an aerial control unit (15). In the figure you can also see a two-way and real-time communication system (3) between the air module (1) and an earth station (2). 10 The aerial control unit (15) is connected with the positioning and guidance system (13) of the aerial module (1), with the radar unit (11) and with the two-way communication module (31). The positioning and guidance system (13) comprises a global positioning system 15 (131), a positioning system based on inertial sensors (132), a positioning system based on real-time satellite kinetic navigation (133) that exchanges information with a real-time satellite kinetic navigation base station (22) located in the earth station (2) and a positioning system based on photogrammetry (134). twenty The radar unit (11) comprises a transmitting antenna (111), a receiving antenna (112) and a radar module (113). The earth station (2) comprises a real-time satellite kinetic navigation base station (22), a flight control system of the aerial module (21), a radar signal processing unit (23), a computer application for the representation of the radar image of the subsoil (24) from the information returned by the radar signal processing unit (23), and a bi-directional and real-time communication system (3) between the air module (1) and the earth station (2). 30 The flight control system of the aerial module (21) comprises a manual flight control system (211) and a system for the generation of trajectories and automatic flight control (212). 35 The radar signal processing unit (23) comprises a set of radar signal processing algorithms (25), which at least consists of a SAR processing algorithm for obtaining the radar image (41) and an algorithm for eliminating the radar image clutter (42). The set of radar signal processing algorithms (25) also comprises an algorithm to correct the blurring of the radar image (43), and an algorithm for the detection of buried objects (45). The set of radar signal processing algorithms (25) also comprises an algorithm for the characterization of the subsoil composition (44). This figure also shows a representation of the soil (50), subsoil (51) and a metallic calibration object (61) used to characterize the composition of the subsoil. Fig. 3 shows an embodiment of the multistatic system in which two aerial modules are used to have a multistatic radar configuration. This figure represents the elements that make up the earth station (2) shown in the figure previous, and the elements that make up the aerial modules, which are also similar to those of the previous figure. In a transmitter air module (101) a radar unit (11) is included, comprising a radar module (113) that generates the radar signal to be transmitted through the transmitting antenna (111), and in the receiving air module (102). ) another radar unit (11) is included, comprising a radar module (113) that receives the radar signal reflected on the ground (50), subsoil (51) and possible objects buried through the receiving antenna (112). This figure shows a two-way and real-time radar communication system (120) between the radar unit (11) embarked on the sending air module (101) and the radar unit (11) shipped on the receiving air module (102) . 10 The two-way and real-time communication system (3) between the sending air module (101) and the receiving air module (102) and the earth station (2) is also represented. fifteen The positioning system based on real-time satellite kinetic navigation (133) of the positioning and guidance system (13) of each aerial module exchanges information with a real-time satellite kinetic navigation base station (22) located at the earth station ( 2). twenty Fig. 4 corresponds to Example 4 described below and represents a comparison between radar images calculated using both the method and the measurement scenario described in said example. The reflectivity of the ground (50) and subsoil (51) is represented in the left graph for the case in which no object has been buried in the subsoil (51), and the 25 is represented in the graphic on the right. reflectivity of the soil (50) and subsoil (51) for the case in which the metallic object has been buried at a depth of 15 cm. The magnitude represented in each graph corresponds to the radar reflectivity normalized in units of decibels, whose scale is represented in the rule of the right 30 with values from -20 to 0. The units of the 'x' and 'z' axes of the graphics come in meters [m]. The dashed line represents the known position where the metallic object is buried. In both graphs, the reflectivity of the soil (50) can be observed, identified as a black band at the position z = 0 m, which occupies the entire width of the graphs. In the case of the graph on the right, the metallic object corresponds to the black region centered at x = 0.5 m, z = -0.17 m. Explanation of a preferred embodiment 40 For a better understanding of the present invention, the following examples of preferred embodiment are described, described in detail, which should be understood without limitation of the scope of the invention. Four. Five Example 1 A first embodiment of the invention was based on the use of a single aerial module (1), consisting of an unmanned aerial vehicle of the multi-rotor type, and more specifically, of an octacopter with its corresponding controller and battery pack. 50 The octacopter used, together with the controller and the batteries, had a maximum weight at takeoff of 6 kg. with a payload capacity of 1.5 kg. Said payload capacity was used to embark and integrate the following elements into the octacopter: - An aerial control unit (15), which was implemented by means of a microcontroller (Raspberry Pi type) and programmed to collect information from the radar unit (11) and from the positioning and guidance system (13), control parameters of flight of the air module (1), and that exchanged information with an earth station (2). The octacopter incorporated a three-axis stabilizer system on which the radar unit (11) was mounted to partially compensate for the oscillations produced during the flight. 10 - An IEEE 802.11 (Wi-Fi) interface that belonged to the bi-directional and real-time communication system (3) between the air module (1) and the earth station (2). This interface was connected to the air control unit (15). - A positioning and guidance system (1 3) of the aerial module. This system was formed by four subsystems, described below: i) positioning system based on inertial sensors (132) that were incorporated into the octacopter controller; ii) global positioning system (131): the GPS receiver included in the octacopter controller was used; iii) positioning system based on real-time satellite kinetic navigation (133) to exchange information with a real-time satellite kinetic navigation base station (22) located at the earth station (2): two RTK units were acquired, one of which it was located in the earth station, and the other in the aerial module (1). These RTK units used a 433 MHz Wi-Fi, Bluetooth or transceiver radio link to send the GPS coordinate correction information to the RTK base station receiver to the GPS unit with RTK functionality shipped on the aerial module (1 ). Therefore, the information provided by the RTK unit and the information provided by the GPS were combined to obtain the geo-referenced coordinates of the air module (1); iv) positioning system based on photogrammetry (134): it was implemented by embarking on the octacopter a webcam, which allows sending photographs every time a measurement of the radar unit (11) is launched. From the digital processing of two or more images taken at different time intervals it was possible to determine the displacement of the octacopter from one position to another, indicating as relative displacements in the plane parallel to the ground (50) (horizontal plane). 35 The spatial information provided by the four positioning subsystems (131) to (134) was processed by a data fusion technique implemented in a microcontroller (Raspberry Pi type) that returns a single set of geo-referenced spatial coordinates of the aerial module (1 ). 40 - With respect to the radar unit (11l), the radar module (113) was implemented using a broadband radar module (of the PulsOn P410 type), which operated in the 3 to 5 GHz band. This module can be controlled in remotely, so that the firing order (generation of the radar signal) and the request for sending data (radar signal received and digitized) could be sent. As the transmitting antenna (111), a 45-pin antenna (circular polarization to the left) of 12 dB gain was used, with parameter S11 in the band 3 to 5 G Hz below -12 dB. The receiving antenna (112) that was used was practically the same as the transmitter, but with right-hand circular polarization. The earth station (2) and the elements that compose it were implemented and integrated 50 as follows: - Flight control system (21) of the aerial module (1). For the manual flight control system (211), the remote control that came standard with the octacopter was used. With respect to the system for the generation of trajectories and automatic flight control (212), a computer application was developed that allows the user to specify the coordinates of the trajectory to be followed by the aerial module (1) over 5 the area under study. The system was configured to operate using the coordinates provided by the system for path generation and automatic flight control (212), giving priority to the manual flight control system (211) in order to regain control over the aerial module (1) if necessary. 10 - Radar signal processing unit (23). It was implemented in a portable computer, which executed the radar signal processing algorithms (25). These algorithms were programmed using a high-level programming language (the one provided by the Matlab company). fifteen - Computer application for the representation of the radar image of the subsoil (24). A graphic computer application was developed that allows the system operator to visualize the reflectivity of the soil (50), subsoil (51), and possible buried objects. The computer application was developed in such a way that the user has different display options (volumetric, representation in cuts according to horizontal, 20 vertical planes or combination of both). Likewise, the computer application highlights the objects found based on the information provided by the algorithm for the detection of buried objects (45) that was executed in the radar signal processing unit (23). 25 - Real-time satellite kinetic navigation base station (22): it consisted of one of the two RTK units mentioned above. The other RTK unit embarked on the aerial module (1). - An IEEE 802.11 (Wi-Fi) interface that belonged to the two-way, real-time communication system (3) 30 between the air module (1) and the earth station (2). This interface was connected to the laptop that implemented the radar signal processing unit (23) and the system for the generation of trajectories and automatic flight control (212), and also to the control command that implemented the flight control system manual (211) of the air module. 35 Example 2 For this embodiment, the system described in example 1 was used, although changing the helix type receiver antenna (112) to a receiver antenna (112) array of two elements: one element consisted of a helix type antenna with circular polarization to right, and the other element consisted of a propeller antenna with circular polarization to the left, both with gain and S11 similar to the transmitting antenna. Each of the elements of the array was connected to a switch or switch that allowed to acquire the radar signal received in one element of the array or in the other element of the array. Four. Five Example 3 For this embodiment, a system similar to that described in example 1 was used although using two aerial modules of the octacopter type: an aerial module (1) that was a transmitter air module (101) with a radar unit (11) that transmitted a signal radar, and another air module (1) that was a receiver air module (102) with a radar unit (11) that captured the radar signal. Synchronization between the sending air module (101) and the receiving air module (102) was achieved by means of communication comprising a bi-directional and real-time radar communication system (120) between the radar module (113) embarked on the sending air module (101) and the radar module (113) embarked on the receiving air module (102). This communication system was integrated into the functionality of the radar module (113) (PulsOn P410 type), so that this existing functionality could be used to extend the system to multistatic mode 10. The determination of the position of both the sending air module (101) and the receiving air module (102) was carried out in the same way as described in example 1, so that the information was available at the earth station (2) of the three-dimensional location of the emitting air module (101) and the receiving air module (102) with an accuracy of value equal to or less than three centimeters. Example 4 twenty To apply the method for the detection, location and imaging of buried objects, the system described in example 1 was used with an aerial module (1). The method comprised the following stages: a) In a first stage a radar signal generated by the radar unit (11) 25 was emitted towards the ground (50) that was to be inspected. b) The signal was reflected in the ground (50), subsoil (51) and possible objects buried in it, and was captured through the radar unit (11). The received radar signal was processed in the radar module (113) to convert it into a digital sequence that could be sent using the communication system between the air module (1) and the earth station (2). In addition, the three-dimensional location of the aerial module (1) was determined with an accuracy of value equal to or less than 3 cm for the positions of the path considered. 35 c) The digital sequence corresponding to the received radar signal that was processed in the radar module (113) and the precise three-dimensional location of the air module (1) were sent to the earth station (2) using the two-way communication system (3) and in real time. 40 d) The radar signal was received at the earth station (2) and processed in the radar signal processing unit (23) to obtain a three-dimensional image of the subsoil (51) and detect and locate possible buried objects through a set of algorithms of radar signal processing (25) comprising a SAR processing algorithm for obtaining the radar image (41) and a clutter elimination algorithm of the radar image (42). Once the radar signal and three-dimensional location data of the aerial module (1) at the earth station (2) were received, the position of the aerial module (1) was varied and steps a), b) and c) were repeated prior to stage d). fifty The trajectory positions described by the aerial module (1) were created using the system for the generation of trajectories and automatic flight control (212). Positions located at different heights on the same point on the ground (50) were considered, thereby increasing the diversity of information that allowed improving the ability to detect, locate and obtain the image of the soil (50) and objects 5 buried in the subsoil (51). The radar signal data received at the earth station (2) for each position of the air module (1) was stored in a matrix, where each row of the matrix corresponded to a position of the air module (1). Likewise, the three-dimensional location data of the aerial module (1) was stored in a coordinate matrix. Using the information of the positions of the aerial module, and known the size of the subsoil (51) to be inspected, a transformation matrix was constructed that related the points of the subsoil (51) with the positions of the aerial module (1). The SAR processing algorithm (41) performed mathematical operations with the transformation matrix and the matrix of the digitized radar signals and the reflectivity of the soil (50) and subsoil (51) was calculated. This reflectivity was further processed using the radar image clutter elimination algorithm (42) to highlight the possible presence of buried objects and eliminate soil reflection (50). twenty To compensate for the blurring of the radar image due to the uncertainty associated with the positioning and guidance system (13) of the aerial module (1), the SAR processing algorithm (41) and the clutter elimination algorithm (42) were combined with an algorithm to correct the blurring of the radar image (43) due to the uncertainty associated with the positioning and guidance system (13). The algorithm to correct the blurring of the radar image (43) implemented the method called Phase Gradient Autofocus (PGA), which consisted of identifying characteristic points in different radar images, so that it corrected the blur by applying poisoning and offset operations. 30 Using an algorithm for the detection of buried objects (45) the three-dimensional image was processed in search of clusters of points with high reflectivity, which could correspond to buried objects. The algorithm for the detection of buried objects (45) analyzed the shape of the area or volume with high reflectivity and, based on training patterns stored in a database, decided whether it corresponded to a potential buried object or not. These training patterns were obtained from photographs of different types of buried objects (antipersonnel mines, archaeological remains, pipes, etc.) and could be calculated prior to scanning the area under study. 40 Finally, the reflectivity of the soil (50), subsoil (51) and possible objects buried in it was shown as a three-dimensional image of the subsoil (51) in the computer application for the representation of the radar image of the subsoil (24), where also objects that had been detected by the algorithm for the detection of buried objects (45) were highlighted. Four. Five The method described in this example was applied by flying the aerial module (1) over a sandy subsoil (51) of homogeneous composition (geographical location: Ñora beach, Gijón, Asturias). The trajectory consisted of a horizontal displacement of 1 m along a reference axis 'x', at a height of 0.5 m above the ground (50) that had an irregularity of approximately 5 cm (microdunes). An object was buried metallize 15 cm in diameter and 2 cm thick at a depth of 15 cm in the sandy subsoil (51). The reflectivity of the subsoil was represented in the 'x-z' plane, where 'z' corresponded to the height axis with respect to the average height of the ground (50) (see Figure 4). The reflectivity of the ground (50) and subsoil (51) is represented in the graph on the left for the case in which no object was buried in the subsoil (51), and the reflectivity is represented on the right from the ground (50) and subsoil (51) for the case in which the metallic object described in the subsoil (51) was buried. The ability of the described method to detect the metallic object buried in the subsoil 10 (51), denoted with a dashed line, could be checked. In both graphs, the reflectivity of the soil (50) was observed, identified as a black band at the position z = 0 m, which occupied the entire width of the graph. In the case of the graph on the right, the metallic object corresponded to a black region centered at x = 0.5 m, z = -0.17 m. fifteen Example 5 For this embodiment, the method described in example 4 was used, but the multistatic system described in example 3 was considered, with an air transmitter module (101) and a receiver air module (102). In this example, steps a), b) and c) prior to step d), described in example 4, were modified as follows: 25 a) In a first stage a radar signal generated by the radar unit (11) embarked on the emitting air module (101) was emitted towards the ground (50) that was to be inspected. b) The signal was reflected in the ground (50), subsoil (51) and possible objects buried in it, and was captured through the radar unit (11) embarked on the receiving aerial module (102). Synchronization between the radar unit (11) shipped in the sending air module (101) and the radar unit (11) shipped in the receiving air module (102) was performed using the two-way and real-time radar communication system (120) . The received radar signal was processed in the radar module (113) of the radar unit (11) embarked on the receiving air module (102). In addition, the three-dimensional location of the emitting air module (101) and the receiving air module (102) was determined with a precision of value equal to or less than 3 cm for the positions of the path considered. 40 c) The digital sequence corresponding to the received radar signal that is processed in the radar module (113) of the radar unit (11) embarked on the receiving air module (102) and the precise three-dimensional location of the sending air module (101) and of the receiving air module (102) were sent to the earth station (2) using the two-way and real-time communication system (3). Four. Five Step d) was not modified with respect to as described in example 4. Once the radar signal and three-dimensional location data of the sending air module (101) and the receiving air module (102) in the earth station (2) were received, the position of the receiving air module (102) was varied and the stages a), b) and c) previously to stage d). The position of the emitting air module (101) was not changed, thus obtaining a multistatic measurement system. In this example, for simplicity, positions at different heights were not considered. All positions of the path described by the receiving air module (102) were at the same height with respect to the ground (50) as the emitting air module (101). 5 The processing of the radar signal data received at the earth station (2) for each position of the receiving air module (102) was performed as described in example 4, except that a coordinate matrix was added row more corresponding to the position of the emitting air module (101), the remaining 10 rows of said matrix being filled with the positions of the receiving air module (102). Example 6 For this embodiment, the method described in example 4 was used, but the polarimetric information obtained by means of the system described in example 2 was considered. In this example, for each position of the aerial module (1), steps a), b) and c) were carried out prior to stage d), described in example 4. twenty In stage b), the signal was reflected in the ground (50), subsoil (51) and possible objects buried in it. The reflected signal was received captured in the radar unit (11) through the two array elements of the receiving antenna (112) described in example 2. First, the switch switched to the array element consisting of a helix type antenna with circular polarization to the right, and secondly, the switch 25 commuting to the array element consisting of a helix type antenna with circular polarization to the left. The radar signal data received at the earth station (2) for each position of the air module (1) and for each element of the array of the receiving antenna (112) was stored in a matrix. The SAR processing algorithm (41) performed mathematical operations with the transformation matrix and the matrix of the digitized radar signals and calculated the reflectivity of the soil (50) and subsoil (51) for each polarization, combining them in amplitude. Once combined, the resulting reflectivity was processed in the same manner as described in the method of Example 4. 35 Example 7 To apply the method for the characterization of the subsoil (51) the system described in example 1 was used. The method comprised the following steps: a) a metallic calibration object (6 1) was buried in the subsoil (51); b) a radar signal generated by a radar unit (11) was emitted towards the ground (50) where the metallic calibration object (61) was buried; Four. Five c) the radar signal reflected on the ground (50), subsoil (51) and on the metallic calibration object (61) was captured through a radar unit (11) and the precise three-dimensional location of the aerial module was determined ( 1) with an accuracy of value equal to or less than three centimeters; fifty d) the radar signal and the precise three-dimensional location of the air module (1) were sent to the earth station (2) using the communication system (3); e) the radar signal was processed in the radar signal processing unit (23) to characterize the composition of the subsoil (51) by means of an algorithm for the characterization of the subsoil composition (44) in which the echo was considered in the floor (50) and the echo in a metallic calibration object (61). The algorithm for the characterization of the subsoil composition (44) carried out the estimation of the permittivity of the subsoil (51) from the determination of the distance 10 and / or the difference in amplitude between the echo in the soil ( 50) and the echo in a metallic calibration object (61). The calculated permittivity value was used as the input value for the application of the SAR processing algorithm (41) and the clutter elimination algorithm (42). fifteen The method described in this example was applied by flying the aerial module (1) over a sandy subsoil (51) of homogeneous composition (geographical location: Ñora beach, Gijón, Asturias). Based on the recommendation published in (Calculation of soil moisture [recovered 2016-15-1]. Recovered from the Internet: <http://maizedoctor.org/ 20 en / estimation-of-moisture-of- soil />), it was estimated that the moisture content of the sandy subsoil (51) was between 6 and 8%. The metallic calibration object (61) was buried at 15 cm. After applying the method described in this example, a range of permittivity of the sandy subsoil (51) estimated between 5.4 and 6.2 was obtained. 25 The estimated permittivity with the method described in this example was compared with the reference value published in the article by Fratticcioli, E., Dionigi, M., & Sorrentino, R. (2003, October). A new permittivity model for the microwave moisture measurement of wet sand, Proceedings of 33rd European Microwave Conference, 2003. (pp. 539-542). In said article, for a sandy subsoil (51) with a moisture content between 6 and 30 8% a range of permittivity was provided between 5 and 7, in accordance with the range obtained after applying the method (5.2 to 6.4).
权利要求:
Claims (41) [1] 1. Airborne system for detection, location and imaging of buried objects comprising: 5 - an aerial module (1) which in turn comprises a radar unit (11) that emits and captures radar signals, a positioning and guidance system (13) of the aerial module (1), and an aerial control unit (15) that collects information from the radar unit (11) and the positioning and guidance system (13), controls flight parameters of the aerial module (1) and exchanges information with an earth station (2); 10 - an earth station (2) which in turn comprises a flight control system (21) of the air module (1), a radar signal processing unit (23) received from the radar unit (11) that processes the signals radar using a set of radar signal processing algorithms (25), and a computer application for the representation of the radar image of the subsoil (24) obtained from the radar signal processing unit (23) and; - communication means for transmitting and receiving wireless signals between the air module (1) and the earth station (2); twenty characterized in that the positioning and guidance system (13) of the aerial module (1) comprises a global positioning system (131), a positioning system based on inertial sensors (132), a positioning system based on kinetic satellite navigation in real-time (133) that exchanges information with a real-time satellite kinetic navigation base station (22) located in the earth station (2) and a positioning system based on photogrammetry (134), which sends information to the unit of aerial control (15) providing the precise three-dimensional location of the aerial module (1) and the georeferencing of the data obtained with the radar unit (11) with an accuracy of value equal to or less than three centimeters, and 30 why a processing algorithm radar signal (25) of the radar signal processing unit (23) is a SAR processing algorithm for obtaining the radar image (41) and another is an algorithm of Clutter removal of the radar image (42). [2] 2. Airborne system for detection, location and imaging of 35 buried objects comprising: - an air module (1), which is an air transmitter module (101), which in turn comprises a radar unit (11) that emits radar signals, a positioning and guidance system (13) of the air transmitter module (101) , and an aerial control unit (15) that collects information from the radar unit (11) and the positioning and guidance system (13), controls flight parameters of the emitting air module (101) and exchanges information with an earth station (2); - an air module (1), which is a receiver air module (102), which in turn comprises a radar unit (11) that captures the radar signal, a positioning and guidance system (13) of the receiver air module ( 102), and an aerial control unit (15) that collects information from the radar unit (11) and the positioning and guidance system (13), controls flight parameters of the receiving air module (102) and exchanges information with a station earth (2); fifty - an earth station (2) which in turn comprises a flight control system (21) of the sending air module (101) and of the receiving air module (102), a radar signal processing unit (23) received from the radar unit (11) that processes the radar signals by means of a set of radar signal processing algorithms (25), and a computer application for the representation of the radar image of the subsoil 5 (24) obtained from the processing unit of radar signals (23); Y - communication means for transmitting and receiving wireless signals between the sending air module (101) and the earth station (2), between the receiving air module (102) and the earth station (2), and between the sending air module ( 101) and the aerial receiver module 10 (102); characterized in that the positioning and guidance system (13) of the sending air module (101) and the receiving air module (102) comprises a global positioning system (131), a positioning system based on inertial sensors 15 (132), a positioning system based on real-time satellite kinetic navigation (133) that exchanges information with a real-time satellite kinetic navigation base station (22) located on the earth station (2) and a positioning system based on photogrammetry (134 ), which send information to the air control unit (15) providing the precise three-dimensional location of the sending air module 20 (101) and the receiving air module (102) and the georeferencing of the data obtained with the radar unit (11) with a precision of value equal to or less than three centimeters, and why a radar signal processing algorithm (25) of the radar signal processing unit (23) is an algorithm SAR processing method for obtaining the radar image (41) and another is a clutter elimination algorithm of the radar image 25 (42). [3] 3. System according to claims 1 or 2 characterized in that the aerial module (1) is an unmanned aerial vehicle. 30 [4] 4. System according to claim 3 characterized in that the unmanned aerial vehicle is a multi-rotor. [5] 5. System according to claim 1 characterized in that the communication means comprise a two-way and real-time communication system (3) between the air module (1) and the earth station (2). [6] 6. System according to claim 2 characterized in that the communication means comprise a two-way and real-time communication system (3) between the sending air module (101) and the earth station (2), a communication system (3) 40 bi-directional and real-time between the receiving air module (102) and the earth station (2), and a two-way, real-time radar communication system (120) between the radar unit (11) embarked on the sending air module ( 101) and the radar unit (11) embarked on the aerial receiver module (102). Four. Five [7] System according to claim 5 or 6, characterized in that the communication system (3) or the radar communication system (120) comprises one or several 3G / 4G communication modules or one or several low frequency transceivers or an IEEE interface 802.11 (Wi-Fi) or one or more Zigbee modules or one or more Bluetooth modules, or a combination of the above. fifty [8] 8. System according to claim 1 characterized in that the radar unit (11) comprises: - a transmitting antenna (111) and a receiving antenna (112); 5 - a radar module (113) for the generation of an electromagnetic signal in the working frequency band whose frequency is greater than or equal to 5 GHz, and for the reception of the dispersed electromagnetic signal. [9] 9. System according to claim 2 characterized in that the radar unit (11) 10 embarked on the emitting air module (101) comprises: - a transmitting antenna (111); - a radar module (113) for generating an electromagnetic signal in the working frequency band 15 whose frequency is greater than or equal to 5 GHz. [10] 10. System according to claim 2 characterized in that the radar unit (11) embarked on the receiving aerial module (102) comprises: twenty - a receiving antenna (112); - a radar module (113) for receiving the dispersed electromagnetic signal. [11] 11. System according to claim 1 or 2 characterized in that the flight control system (21) of the air module (1) comprises: - a manual flight control system (211); Y - a system for the generation of trajectories and automatic flight control (212). 30 [12] 12. System according to claim 1 or 2 characterized in that the SAR processing algorithm for obtaining the radar image (41) uses polarimetric information. 35 [13] 13. System according to claim 12 characterized in that the polarimetric information is based on the measurement of the radar signal corresponding to two orthogonal polarizations of the dispersed electric field. [14] 14. System according to claim 1 or 2 characterized in that the set of 40 radar signal processing algorithms (25) further comprise: - an algorithm to correct the blurring of the radar image (43) due to the uncertainty associated with the positioning and guidance system (13) of the aerial module (1); and 45 - an algorithm for the detection of buried objects (45). [15] 15. System according to claim 1 or 2 characterized in that the set of the radar signal processing algorithms (25) further comprises an algorithm for the characterization of the subsoil composition (44). [16] 16. System according to claim 15 characterized in that the algorithm for the characterization of the composition of the subsoil (44) carries out the estimation of the permittivity of the subsoil (51) from the determination of the distance between the echo in the ground (50) and the echo in a metallic calibration object (61), both observable in the radar image. 5 [17] 17. System according to claim 15 characterized in that the algorithm for the characterization of the composition of the subsoil (44) carries out the estimation of the permittivity of the subsoil (51) from the measurement of the difference in amplitude between the echo in the floor (50) and the echo in a metallic calibration object (61). 10 [18] 18. System according to claim 15 characterized in that the algorithm of elimination of the radar image clutter (42) is based on an iterative calculation process in which the effect of the ground (50) on the radar image is identified based on the altitude of the aerial module (1) and the estimation of the subsoil composition (51) provided by the algorithm for the characterization of the subsoil composition (44) and subsequently removed from the image using a mask-based algorithm and an algorithm of SAR processing to obtain the radar image (41). [19] 19. System according to claim 1 characterized in that the aerial module (1) emits and captures radar signals establishing its position at different heights relative to the ground (50). [20] 20. System according to claim 2 characterized in that the emitting air module (101) emits radar signals establishing its position at different heights relative to the ground 25 (50) and the receiving air module (102) captures radar signals establishing its position at different heights relative to the ground (50). [21] 21. System according to claim 19 or 20 characterized in that the radar image created with the radar signals obtained at different heights are combined to detect, locate and obtain the image of the ground (50) and of the objects buried in the subsoil (51 ). [22] 22. System according to claim 1, 2, 19 or 20 characterized in that the SAR processing algorithm for obtaining the radar image (41) is based on the coherent sum 35 of the radar signal measured in do !; or more positions of the aerial module (1), provided that the separation between two consecutive positions is equal to or less than half a wavelength at the highest working frequency. [23] 23. Method for detecting, locating and obtaining images of objects buried by means of the system of claim 1, or by means of the system of claim 2, comprising the following steps: a) issue a radar signal] generated by a radar unit (11) to the ground (50) that is to be inspected; b) capture the radar signal reflected on the ground (50), subsoil (51) and possible buried objects, through a radar unit (11) and determine the precise three-dimensional location of the aerial module (1) with an accuracy of equal value or less 50 to three centimeters; c) send the radar signal and the precise three-dimensional location of the air module (1) to the earth station (2) using the communication system (3); d) process the radar signal in the radar signal processing unit (23) to obtain a three-dimensional image of the subsoil (51) and detect and locate possible 5 buried objects by means of a set of radar signal processing algorithms (25) comprising a SAR processing algorithm for obtaining the radar image (41) and a clutter elimination algorithm of the radar image (42). [24] 24. Method according to claim 23, characterized in that the emission of stage a) is carried out from an air transmitter module (101) with a radar unit (11) that transmits a radar signal and the reception of stage b) is It is carried out by means of an aerial receiver module (102) with another radar unit (11) that captures the radar signal, located in two different positions, and by which the emission and reception are synchronized by means of a radar communication system (120). fifteen [25] 25. Method according to claim 23 or 24, characterized in that the radar unit (11) also processes the radar signal received in step b) to convert it to a digital sequence, and in step d) the radar signal processing unit ( 23) processes the digitized radar signal. twenty [26] 26. Method according to claim 23 or 24 characterized in that the radar signal is a train of electromagnetic pulses. [27] 27. Method according to claim 23 or 24 characterized in that it further comprises varying the position of the air module (1) and repeating steps a), b) and c) prior to step d). [28] 28. Method according to claim 27, characterized in that the radar image created with the radar signals obtained in different positions are combined to detect, locate 30 and obtain the image of the ground (50) and the objects buried in the subsoil (51). [29] 29. Method according to claim 23, 24 or 27 characterized in that the SAR processing algorithm for obtaining the radar image (41) is based on the coherent sum of the radar signal measured in two or more positions of the aerial module (1 ), provided that the separation between two consecutive positions is equal to or less than half a wavelength at the highest working frequency. [30] 30. Method according to claim 23, 24 or 27 characterized in that the SAR processing algorithm for obtaining the radar image (41) uses polarimetric information. [31] 31. Method according to claim 30 characterized in that the polarimetric information is based on the measurement of the radar signal corresponding to two orthogonal polarizations of the dispersed electric field. Four. Five [32] 32. Method according to claim 23, 24 or 27 characterized in that in step d) the radar signal is processed in the radar signal processing unit (23) by means of a set of radar signal processing algorithms (25) which in addition It comprises an algorithm to correct the blurring of the radar image (43) and an algorithm for the detection of buried objects (45). [33] 33. Method according to claim 23, 24 or 27 characterized in that, prior to step a), it further comprises the following steps: e) bury a metallic calibration object (61) in the subsoil (51); 5 f) emit a radar signal generated by a radar unit (11) towards the ground (50) where the metallic calibration object (61) is buried; g) capture the radar signal reflected on the ground (50), subsoil (51) and on the metallic calibration object (61), through a radar unit (11) and determine the precise three-dimensional location of the aerial module (1 ) with an accuracy of value equal to or less than three centimeters; h) send the radar signal and the precise three-dimensional location of the aerial module (1) to the earth station (2) using the communication system (3); fifteen i) process the radar signal in the radar signal processing unit (23) to characterize the composition of the subsoil (51) by means of an algorithm for the characterization of the composition of the subsoil (44) in which the echo in the ground is considered (50) and the echo in a metallic calibration object (61). twenty [34] 34. Method according to claim 33 characterized in that the steps e), f), g), h) and i) to characterize the composition of the subsoil (51), are executed only once, prior to step a). 25 [35] 35. Method according to claim 33 characterized in that the algorithm for characterizing the composition of the subsoil (44) performs the estimation of the permittivity of the subsoil (51) from the determination of the distance between the echo in the ground (50) and the echo in a metallic calibration object (61). 30 [36] 36. Method according to claim 33 characterized in that the algorithm for characterization of the subsoil composition (44) carries out the estimation of the permittivity of the subsoil (51) from the measurement of the amplitude difference between the echo in the floor (50) and the echo in a metallic calibration object (61). 35 [37] 37. Method according to claim 33 characterized in that the algorithm of elimination of the radar image clutter (42) is based on an iterative calculation process in which the ground effect (50) on the radar image is identified based on the altitude of the aerial module (1) and the estimation of the subsoil composition (51) provided by the algorithm for the characterization of the subsoil composition (44), and subsequently 40 is removed from the image using a mask-based algorithm and a SAR processing algorithm for obtaining the radar image (41). [38] 38. Method for characterizing the composition of the subsoil (51) by the system of claim 1 or by the system of claim 2 comprising the following steps: a) bury a metallic calibration object (61) in the subsoil (51); b) emit a radar signal generated by a radar unit (11) towards the ground (50) where 50 the metallic calibration object (61) is buried; c) capture the radar signal reflected on the ground (50), subsoil (51) and on the metallic calibration object (61), through a radar unit (11) and determine the precise three-dimensional location of the aerial module (1) with an accuracy of value equal to or less than three centimeters; 5 d) send the radar signal and the precise three-dimensional location of the aerial module (1) to the earth station (2) using the communication system (3); e) process the radar signal in the radar signal processing unit (23) to characterize the composition of the subsoil (51) by means of an algorithm for the characterization of the subsoil composition (44) in which the echo is considered in the ground (50) and the echo in a metallic calibration object (61). [39] 39. Method according to claim 38 characterized in that the emission in stage b) is carried out from an airborne transmitter module (101) with a radar unit (11) that transmits a radar signal, and the reception of stage e) is It is carried out by means of an aerial receiver module (102) with another radar unit (11) that captures the radar signal, located in two different positions, and by which the emission and reception are synchronized by means of a radar communication system (120). twenty [40] 40. Method according to claim 38 or 39, characterized in that the algorithm for the characterization of the subsoil composition (44) carries out the estimation of the subsoil permittivity (51) from the determination of the distance between the echo in the floor (50) and the echo in a metallic calibration object (61). 25 [41] 41. Method according to claim 38 or 39, characterized in that the algorithm for the characterization of the subsoil composition (44) carries out the estimation of the permittivity of the subsoil (51) from the measurement of the difference in amplitude between the echo in the ground (50) and the echo in a metallic calibration object (61). 30
类似技术:
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申请号 | 申请日 | 专利标题 ES201600073A|ES2577403B2|2016-01-21|2016-01-21|Airborne system and methods for the detection, location and imaging of buried objects and the characterization of the subsoil composition|ES201600073A| ES2577403B2|2016-01-21|2016-01-21|Airborne system and methods for the detection, location and imaging of buried objects and the characterization of the subsoil composition| CN201780019054.4A| CN109073348B|2016-01-21|2017-01-18|Airborne system and method for detecting, locating and image acquisition of buried objects, method for characterizing subsoil composition| PCT/ES2017/000006| WO2017125627A1|2016-01-21|2017-01-18|Airborne systems and detection methods localisation and production of images of buried objects and characterisation of the composition of the subsurface| US16/071,686| US10895636B2|2016-01-21|2017-01-18|Airborne systems and detection methods localization and production of images of buried objects and characterization of the composition of the subsurface| EP17741130.3A| EP3407007B1|2016-01-21|2017-01-18|Airborne systems and detection methods for detection localisation and production of images of buried objects and characterisation of the composition of the subsurface| 相关专利
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