A distributed airborne SAR target positioning method and device

Abstract

The present application relates to the technical field of radar signal processing, and provides a kind of distributed airborne SAR target positioning method and device, applied to distributed airborne SAR system, system includes: multiple airborne platforms of SAR, and multiple preset targets to be positioned, according to time delay deception jamming, time delay measurement error interference and the position error interference of airborne platform, the target echo mathematical model between airborne platform and preset target to be positioned is constructed.According to target echo mathematical model, the target echo signal corresponding to multiple airborne platforms is obtained respectively.BP imaging is carried out to the target echo signal corresponding to multiple airborne platforms respectively, and each SAR image corresponding to multiple airborne platforms is obtained, wherein each SAR image includes: multiple preset targets to be positioned.According to multiple SAR images and preset TOA residual error equation group, the least square method is used for iterative solution, and the target positioning result of each preset target to be positioned is obtained.By this way, the accuracy of target positioning result is improved.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, and in particular to a distributed airborne SAR target localization method and apparatus. Background Technology

[0002] In the field of Synthetic Aperture Radar (SAR), distributed airborne SAR systems, through the collaborative operation of multiple airborne platforms carrying SAR, can effectively expand the synthetic aperture and acquire multi-angle observation information, thereby significantly improving the positioning accuracy and anti-jamming capability of ground targets. The core theoretical framework of the distributed airborne SAR positioning technology system mainly includes ground-to-air positioning theory and air-to-air positioning theory. Ground-to-air positioning theory uses ground control points to map the geometric relationship between the ground mapping area and the SAR image; therefore, the number and spatial distribution of ground control points are key factors affecting positioning accuracy. While air-to-air positioning theory does not rely on ground control points, it is still affected by parameter errors. For example, the positioning performance of the range-Doppler (RD) positioning model directly depends on the accuracy of the range and Doppler parameters. Furthermore, it should be noted that when using distributed unmanned aerial vehicle (UAV) SAR for target positioning, various error interferences exist, such as site measurement errors, time delay measurement errors, and various deceptive interferences. These core errors reduce the accuracy of the target positioning results and directly affect the accuracy of the positioning.

[0003] In existing technologies, distributed airborne SAR target localization can be achieved through a distributed UAV-borne SAR target time difference self-localization method. Specifically, a "one-transmit, four-receive" target echo model is first constructed, incorporating UAV site errors and time-frequency synchronization errors. Then, the initial target position is obtained through back projection imaging. Next, a set of localization equations is established by combining echo distance information and UAV site information. Finally, the target position is obtained by iteratively solving the set of localization equations.

[0004] However, when using existing technologies, the accuracy of target positioning is affected because various deceptive interferences in complex electronic warfare scenarios are not taken into account, making it difficult to obtain relatively accurate target positioning results. Summary of the Invention

[0005] Therefore, it is necessary to provide a distributed airborne SAR target localization method and device to address the aforementioned technical problems.

[0006] In a first aspect, embodiments of the present invention provide a distributed airborne SAR target localization method, the method comprising: An application to a distributed airborne SAR system, the system comprising: multiple airborne platforms equipped with SAR and multiple preset targets to be located, the method comprising: Based on time delay spoofing interference, time delay measurement error interference, and airborne platform position error interference, a target echo mathematical model between the airborne platform and the preset target to be located is constructed. Based on the target echo mathematical model, target echo signals corresponding to multiple airborne platforms are obtained respectively; BP imaging is performed on the target echo signals corresponding to the multiple airborne platforms respectively to obtain SAR images corresponding to the multiple airborne platforms respectively, wherein each SAR image includes: multiple preset targets to be located; Based on multiple SAR images and a set of preset TOA residual equations, the target location results of each preset target to be located are obtained by iteratively solving the least squares method.

[0007] In one embodiment, constructing a mathematical model of the target echo between the airborne platform and the preset target to be located, based on time delay spoofing interference, time delay measurement error interference, and position error interference of the airborne platform, includes: The time delay deception interference distance is determined based on the distance between the airborne platform and the preset target to be located, as well as the time delay deception interference signal of at least one deception interference source. The position error interference distance, including the time delay spoofing interference, is determined based on the error distance between the airborne platform and the preset target to be located and the time delay spoofing interference distance. Determine the interference distance of the time delay measurement error based on the interference of the time delay measurement error; The target echo mathematical model is constructed based on the position error interference distance and the time delay measurement error interference distance.

[0008] In one embodiment, the mathematical model of the target echo can be defined by the following expression:

[0009] in, Indicates the first The amplitude of the target echo signal corresponding to each airborne platform The range window function represents the radar signal transmitted by the airborne platform. Indicates a fast time interval. Indicates the first The first moment The airborne platform and the first The position error interference distance between the preset targets to be located Indicates the first The first moment The airborne platform and the first The time delay measurement error interference distance between the preset targets to be located Let represent the azimuth window function of the radar signal transmitted by the airborne platform, and let c represent the speed of light. The wavelength corresponding to the center frequency of the radar signal. This indicates the frequency modulation (FM) of the radar signal.

[0010] In one embodiment, the time delay spoofing interference distance can be defined by the following expression:

[0011] in, Indicates the first The airborne platform and the first Between the first preset target to be located The time delay parameter of the interference signal, Indicates the first The first moment The airborne platform and the first The distance between preset targets to be located; The location error interference distance can be defined by the following expression:

[0012] in, Indicates the first The first moment The airborne platform and the first Error distance between preset targets to be located; The time delay measurement error interference distance can be defined by the following expression:

[0013] in, Indicates the first The first moment The airborne platform and the first The time delay measurement error between preset targets to be located.

[0014] In one embodiment, before obtaining the target localization results of each preset target to be located by iteratively solving the least squares method based on multiple SAR images and a preset TOA residual equation set, the method further includes: Construct the preset TOA residual equation set, which includes: multiple preset TOA residual equation subsets corresponding to the airborne platforms respectively, and each preset TOA residual equation subset includes: multiple preset TOA residual equations between each airborne platform and multiple preset targets to be located; The preset TOA residual equation set can be defined by the following expression:

[0015] in, Indicates the first The actual coordinates of each airborne platform Indicates relative to the first The first airborne platform, based on the SAR image, acquired the first... The preset coordinates of the target to be located. Indicates the time at the center of the imaging The airborne platform mentioned above and the first The measured distance between the preset targets to be located.

[0016] In one embodiment, the preset target to be located is either a real target or a false target. The step of iteratively solving the least squares method based on multiple SAR images and a preset TOA residual equation set to obtain the target location result for each preset target includes: For the SAR image, at least one real target to be located is determined from multiple preset targets to be located using the preset TOA residual equation set; For each real target to be located, a nonlinear positioning equation set is constructed based on the preset TOA residual equation set. Based on the aforementioned nonlinear positioning equations, the least squares method is used for iterative solution to obtain the target positioning results for each real target to be located.

[0017] In one embodiment, determining at least one real target to be located from multiple preset targets to be located using the preset TOA residual equations for the SAR image includes: The SAR image is preprocessed, and the coordinate positions of each preset target to be located are obtained by two-parameter CFAR. For each of the airborne platforms, the measured distance between each airborne platform and each of the preset targets to be located is obtained based on the single-pulse echo signal of the airborne platform at the imaging center time. Based on the measured distance, the coordinate position, and the preset TOA residual equations, calculate the distance residual between the airborne platform and the preset target to be located; When the distance residuals between multiple airborne platforms and the same preset target to be located are all less than a preset threshold, the current preset target to be located is determined to be the real target to be located.

[0018] In one embodiment, constructing a nonlinear positioning equation set for each real target to be located, based on the preset TOA residual equation set, includes: For each real target to be located, the target preset TOA residual equation corresponding to each real target to be located is determined in the multiple preset TOA residual equation subgroups respectively; Based on multiple target preset TOA residual equations, a set of nonlinear positioning equations is constructed for each real target to be located.

[0019] In one embodiment, the step of iteratively solving the nonlinear positioning equations using the least squares method to obtain the target positioning results for each real target to be located includes: For each real target to be located, a target preset TOA residual equation is used to determine the initial target position of the real target to be located. Then, a Taylor expansion is performed on the target preset TOA residual equation at the initial target position to determine the pseudo-linear positioning equation. Based on multiple pseudo-linear positioning equations, construct a set of pseudo-linear positioning equations and obtain the matrix equations of the set of pseudo-linear positioning equations. The matrix equation is solved iteratively using the least squares method to obtain the target localization results for each real target to be located.

[0020] Secondly, embodiments of the present invention provide a distributed airborne SAR target localization device, applied to a distributed airborne SAR system, the system comprising: multiple airborne platforms equipped with SAR and multiple preset targets to be located, the device comprising: The target echo mathematical model construction module is used to construct a target echo mathematical model between the airborne platform and the preset target to be located based on time delay deception interference, time delay measurement error interference and airborne platform position error interference. The target echo signal acquisition module is used to acquire target echo signals corresponding to multiple airborne platforms respectively, based on the target echo mathematical model. Multiple SAR image acquisition modules are used to perform BP imaging on the target echo signals corresponding to the multiple airborne platforms respectively, and acquire each SAR image corresponding to the multiple airborne platforms respectively, wherein each SAR image includes: multiple preset targets to be located; The target localization result acquisition module is used to obtain the target localization result of each preset target to be located by iteratively solving the least squares method based on multiple SAR images and a preset TOA residual equation set.

[0021] The technical solution provided by the embodiments of the present invention has the following advantages compared with the prior art: This invention provides a distributed airborne SAR target localization method, applied to a distributed airborne SAR system. The system includes multiple airborne platforms equipped with SAR and multiple preset targets to be located. Based on time delay spoofing interference, time delay measurement error interference, and position error interference of the airborne platforms, a mathematical model of target echoes between the airborne platforms and the preset targets to be located is constructed. According to the target echo mathematical model, target echo signals corresponding to each of the multiple airborne platforms are acquired. Backpropagation (BP) imaging is performed on the target echo signals corresponding to each of the multiple airborne platforms to acquire individual SAR images corresponding to each airborne platform. Each SAR image includes multiple preset targets to be located. Based on the multiple SAR images and a preset TOA residual equation set, the target localization result of each preset target to be located is obtained by iteratively solving using the least squares method. This approach fully considers the impact of time delay measurement error interference and airborne platform position error interference on the target positioning results, while also taking into account the effect of time delay deception interference on the target positioning results. It can effectively avoid the problem that existing technologies, due to their failure to consider time delay deception interference, result in false targets with similar characteristics to the real target in the SAR images acquired by the airborne platform, thus affecting the target positioning accuracy and improving the accuracy of the target positioning results. Attached Figure Description

[0022] Figure 1 A flowchart illustrating a distributed airborne SAR target localization method provided in an embodiment of the present invention; Figure 2 A schematic diagram of a scenario for a distributed airborne SAR target localization method provided in an embodiment of the present invention; Figure 3 The image shown is a schematic diagram of the result of BP imaging provided in an embodiment of the present invention; Figure 4 The diagram shown is a structural schematic of a distributed airborne SAR target positioning device provided in an embodiment of the present invention. Detailed Implementation

[0023] To better understand the above-mentioned objectives, features, and advantages of the present invention, the solutions of the present invention will be further described below. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other.

[0024] Many specific details are set forth in the following description in order to provide a full understanding of the invention, but the invention may also be practiced in other ways different from those described herein; obviously, the embodiments in the specification are only some embodiments of the invention, and not all embodiments.

[0025] In one embodiment, such as Figures 1-2 As shown, Figure 1This is a flowchart illustrating a distributed airborne SAR target localization method provided in an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating a scenario for a distributed airborne SAR target localization method provided in an embodiment of the present invention. The method is applied to a distributed airborne SAR system, which includes multiple airborne platforms equipped with SAR and multiple preset targets to be located. For example, for the multiple airborne platforms equipped with SAR, such as airborne platforms... Airborne platform Airborne platform Multiple SAR-equipped airborne platforms move at uniform speeds in different directions. Each platform employs a self-transmitting and self-receiving mode, meaning it transmits radar information and receives corresponding echo signals. In this way, multiple SAR-equipped airborne platforms can acquire SAR images containing multiple pre-defined targets to be located within the imaging area from different perspectives. These pre-defined targets include... It should be noted that, in this embodiment, the origin is taken as the center of the imaging area. Establish a Cartesian coordinate system to locate the position information of multiple airborne platforms and multiple preset targets to be located.

[0026] Based on this, the present invention specifically includes the following steps: S10: Based on the interference of time delay spoofing, time delay measurement error, and position error of the airborne platform, construct a mathematical model of the target echo between the airborne platform and the preset target to be located.

[0027] Among these, time delay spoofing interference refers to interference located on various preset targets that can forward multiple signals with different time delays to various airborne platforms. Due to this interference, false targets with similar characteristics to the real targets will appear in the SAR images acquired by each airborne platform, directly affecting the accuracy of the target localization results. Time delay measurement error interference arises from the delay error that occurs during the process of radar signals emitted by each airborne platform being reflected by the preset targets within the imaging area and the corresponding echo signals being received. Airborne platform position error interference refers to the inaccuracy of the airborne platform's position, which affects the accuracy of the target localization results.

[0028] Specifically, for the airborne platform and the preset target to be located, a target echo mathematical model is constructed based on the interference of time delay spoofing, time delay measurement error, and position error of the airborne platform. The target echo signal between the airborne platform and the preset target to be located is then received through the target echo mathematical model.

[0029] Optionally, based on the above embodiments, in some embodiments of the present invention, one implementation of S10 may be: S101: Determine the time delay deception interference distance based on the distance between the airborne platform and the preset target to be located, as well as the time delay deception interference signal of at least one deception interference source.

[0030] Specifically, for each airborne platform, the distance between each airborne platform and each preset target to be located is obtained. Based on the distance between each airborne platform and each preset target to be located, and the time delay spoofing interference signal of one or more spoofing interference sources, the time delay spoofing interference distance is determined.

[0031] Optionally, based on the above embodiments, in some embodiments of the present invention, the time delay spoofing interference distance can be defined by the following expression:

[0032] in, Indicates the first The airborne platform and the first Between the first preset target to be located The time delay parameter of the interference signal, Indicates the first The first moment The airborne platform and the first The distance between preset targets to be located It represents the speed of light.

[0033] S102: Determine the position error interference distance including time delay spoofing interference based on the error distance between the airborne platform and the preset target to be located and the time delay spoofing interference distance.

[0034] Optionally, based on the above embodiments, in some embodiments of the present invention, the position error interference distance can be defined by the following expression:

[0035] in, Indicates the first The first moment The airborne platform and the first The error distance between the preset targets to be located.

[0036] Optionally, based on the above embodiments, in some embodiments of the present invention, the error distance can be determined according to the formula. Sure.

[0037] in, Indicates the first The coordinates of each airborne platform , which represents the distance error parameter between the airborne platform and the preset target to be located.

[0038] S103: Determine the interference distance of the time delay measurement error based on the time delay measurement error interference.

[0039] Optionally, based on the above embodiments, in some embodiments of the present invention, the interference distance of the time delay measurement error can be defined by the following expression:

[0040] in, Indicates the first The first moment The airborne platform and the first The time delay measurement error between the preset targets to be located .

[0041] S104: Construct a mathematical model of the target echo based on the interference distance of the position error and the interference distance of the time delay measurement error.

[0042] Specifically, after determining the interference distance of the position error and the interference distance of the time delay measurement error, a mathematical model of the target echo is constructed based on the interference distance of the position error and the interference distance of the time delay measurement error.

[0043] Optionally, based on the above embodiments, in some embodiments of the present invention, the target echo mathematical model may be defined by the following expression:

[0044] in, Indicates the first The amplitude of the target echo signal corresponding to each airborne platform The range window function represents the radar signal transmitted by the airborne platform. Indicates a fast time interval. Indicates the first The first moment The airborne platform and the first The position error interference distance between the preset targets to be located Indicates the first The first moment The airborne platform and the first Interference distance of time delay measurement error between preset targets to be located Let represent the azimuth window function of the radar signal transmitted by the airborne platform, and let c represent the speed of light. The wavelength corresponding to the center frequency of the radar signal. This indicates the frequency modulation (FM) of the radar signal.

[0045] S11: Based on the target echo mathematical model, obtain the target echo signals corresponding to multiple airborne platforms respectively.

[0046] Specifically, for multiple airborne platforms, the target echo signals corresponding to each airborne platform are obtained based on the target echo mathematical model.

[0047] S12: Perform BP imaging on the target echo signals corresponding to multiple airborne platforms to obtain SAR images corresponding to each airborne platform.

[0048] Each SAR image includes multiple preset targets to be located.

[0049] Specifically, after obtaining the target echo signals corresponding to multiple airborne platforms, BP imaging is performed based on the target echo signals corresponding to multiple airborne platforms to obtain each SAR image corresponding to the multiple airborne platforms.

[0050] For example, refer to Figure 3 As shown, assume there are three airborne platforms, such as airborne platform Airborne platform and airborne platforms Then, BP imaging is performed on the target echo signals corresponding to the three airborne platforms to obtain the airborne platform data. Airborne platform and airborne platforms The first, second, and third SAR images are presented from different viewpoints, and each of these images includes four pre-defined targets to be located. , , , However, this invention is not limited to this, and those skilled in the art can make settings according to the actual situation.

[0051] Optionally, based on the above embodiments, in some embodiments of the present invention, one implementation of S12 may be: establishing an imaging grid: dividing the target area into grid points. Phase compensation and coherent accumulation: for time... Phase compensation is performed at each grid point, and the coherent accumulation result is calculated:

[0052] in, and These represent the start and end times of coherent accumulation in the BP image, respectively. Indicates the first Airborne platforms and grid points at all times The slope distance, This indicates the target echo signal.

[0053] S13: Based on multiple SAR images and the preset TOA residual equations, the target positioning results of each preset target to be located are obtained by iteratively solving the least squares method.

[0054] Specifically, after obtaining the SAR images corresponding to multiple airborne platforms, the target positioning results of each preset target to be located are obtained by iteratively solving the least squares method based on the multiple SAR images and the preset TOA residual equations.

[0055] Optionally, based on the above embodiments, in some embodiments of the present invention, before performing S13, the following steps are further included: S20: Construct a pre-defined TOA residual equation system.

[0056] The preset TOA residual equation set includes: multiple preset TOA residual equation subsets corresponding to multiple airborne platforms, and each preset TOA residual equation subset includes: multiple preset TOA residual equations between each airborne platform and multiple preset targets to be located.

[0057] Optionally, based on the above embodiments, in some embodiments of the present invention, one implementation of S20 may be: constructing multiple preset TOA residual equations between each airborne platform and its corresponding preset target to be located. Based on the multiple preset TOA residual equations, determining a preset TOA residual equation subgroup for each airborne platform, and forming a preset TOA residual equation set based on the preset TOA residual equation subgroups corresponding to the multiple airborne platforms respectively.

[0058] Optionally, based on the above embodiments, in some embodiments of the present invention, the preset TOA residual equation system may be limited by the following expressions:

[0059] in, Indicates the first The actual coordinates of each airborne platform Indicates relative to the first The first airborne platform, based on the SAR image, acquired the first... The preset coordinates of the target to be located. Indicates the time at the center of the imaging The airborne platform and the first The measured distance between the preset targets to be located.

[0060] Optionally, based on the above embodiments, the target to be located is preset to be either a real target or a false target. Therefore, in some embodiments of the present invention, one implementation of S13 can be: S131: For SAR images, at least one real target is determined from multiple preset targets to be located by using a set of preset TOA residual equations.

[0061] Specifically, for each SAR image, one or more real targets are determined from among the multiple preset targets to be located included in each SAR image by using a set of preset TOA residual equations.

[0062] Optionally, based on the above embodiments, in some embodiments of the present invention, one implementation of S131 may be: S1311: Preprocess the SAR image and obtain the coordinates of each preset target to be located through two-parameter CFAR.

[0063] Specifically, the SAR image is filtered, subjected to Otsu thresholding and morphological processing, and then the coordinates of each preset target to be located are obtained through two-parameter CFAR.

[0064] It should be noted that the coordinates of each preset target to be located can be the geometric center of that target. For example, refer to Table 1, which shows the coordinates of an airborne platform. Airborne platform and airborne platforms The four corresponding preset targets to be located , , , The target geometric center location.

[0065] Table 1. Preset Geometric Center Position of the Target to be Located

[0066] S1312: For each airborne platform, the measurement distance between each airborne platform and each preset target to be located is obtained based on the single-pulse echo signal of the airborne platform at the imaging center moment.

[0067] Specifically, for each airborne platform, the single-pulse echo signal of the airborne platform at the imaging center moment is acquired, and the single-pulse echo signal is pulse compressed to obtain the measurement distance between each airborne platform and each preset target to be located.

[0068] Optionally, based on the above embodiments, in some embodiments of the present invention, the measurement distance may be defined by the following expression:

[0069] S1313: Based on the measured distance, coordinate position, and preset TOA residual equations, the distance residual between the computer platform and the preset target to be located.

[0070] Specifically, the measured distance and coordinate position are substituted into the preset TOA residual equation set to calculate the distance residual between each airborne platform and each preset target to be located.

[0071] S1314: When the distance residuals between multiple airborne platforms and the same preset target to be located are all less than a preset threshold, the current preset target to be located is determined to be the real target to be located.

[0072] The preset threshold is used to determine the parameters set for the actual target to be located.

[0073] Specifically, multiple distance residuals are compared with a preset threshold. When it is determined that the distance residuals between multiple airborne platforms and the same preset target to be located are all less than the preset threshold, the current preset target to be located is determined to be the real target to be located.

[0074] For example, continue to refer to Figure 3 As shown, following the above embodiments, for airborne platforms Airborne platform and airborne platforms and its corresponding four preset targets to be located. , , , When the airborne platform is satisfied Airborne platform and airborne platforms With the preset target to be located When the distance residuals between them are all less than the preset threshold, it indicates that the preset target to be located is... The target to be located is considered real, while the target to be located is considered false. However, this invention is not limited to this and those skilled in the art can set it according to the actual situation.

[0075] S132: For each real target to be located, construct a nonlinear positioning equation set based on the preset TOA residual equation set.

[0076] Optionally, based on the above embodiments, in some embodiments of the present invention, one implementation of S132 may be: S1321: For each real target to be located, determine the target preset TOA residual equation corresponding to each real target in the multiple preset TOA residual equation subgroups.

[0077] S1322: Based on the preset TOA residual equations of multiple targets, construct a set of nonlinear positioning equations corresponding to each real target to be located.

[0078] Specifically, for each real target to be located, the target preset TOA residual equation corresponding to each real target is determined in multiple preset TOA residual equation subgroups. Using multiple target preset TOA residual equations, a nonlinear positioning equation set corresponding to each real target to be located is constructed.

[0079] S133: Based on the nonlinear positioning equations, the least squares method is used to iteratively solve the problem and obtain the target positioning results for each real target to be located.

[0080] Optionally, based on the above embodiments, in some embodiments of the present invention, one implementation of S133 may be: S1331: For each target to be located, a TOA residual equation is preset for each target. The initial target position of the target is determined. The preset TOA residual equation is Taylor expanded at the initial target position to determine the pseudo-linear positioning equation.

[0081] Specifically, for each real target to be located, a TOA residual equation is preset for each target to determine the initial target position. At the initial target location Taylor expansion is performed on the target preset TOA residual equation to determine the pseudo-linear positioning equation corresponding to each target preset TOA residual equation for each real target to be located.

[0082] S1332: Based on multiple pseudo-linear positioning equations, construct a set of pseudo-linear positioning equations and obtain the matrix equations of the set of pseudo-linear positioning equations.

[0083] Specifically, after obtaining the pseudo-linear positioning equations corresponding to the multiple target preset TOA residual equations for each real target to be located, a set of pseudo-linear positioning equations is constructed based on the multiple pseudo-linear positioning equations, and further matrix transformation is performed on the set of pseudo-linear positioning equations to obtain the matrix equations corresponding to each real target to be located.

[0084] Optionally, based on the above embodiments, in some embodiments of the present invention, the pseudo-linear positioning equation set may be defined by the following expressions:

[0085] in, Indicates the initial target position. Indicates the first The target localization result of a real target to be located in the current iteration.

[0086] Optionally, based on the above embodiments, in some embodiments of the present invention, the matrix equation may be defined by the following expression:

[0087] in, The difference in target localization results between two iterations can be expressed by the following expression:

[0088] in, The weight covariance matrix can be constrained by the following expression:

[0089] in, For the first The mean square error of delay measurement on each airborne platform Then it means the first The mean square error of the position of each airborne platform.

[0090] Optionally, based on the above embodiments, in some embodiments of the present invention, the first matrix... and the first matrix It can be qualified by the following expression:

[0091]

[0092] in, Indicates the first Positional error interference of individual airborne platforms Indicates the first The interference distance of time delay measurement error on an airborne platform Indicates the first The coordinates of each airborne platform Indicates the first The distance between each airborne platform and the initial target position input in each iteration.

[0093]

[0094] S1333: Iteratively solve the matrix equation using the least squares method to obtain the target localization results for each real target to be located.

[0095] Specifically, the matrix equation is solved iteratively using the least squares method, and the current location result of the actual target to be located obtained in each iteration is used as the initial target position for the next iteration. And obtain the difference in target location results. When the difference in target location results When the value is less than the preset value for stopping the iteration, the iteration stops, and the target location results of each real target to be located are obtained.

[0096] Thus, the distributed airborne SAR target localization method provided in this embodiment is applied to a distributed airborne SAR system, which includes multiple airborne platforms equipped with SAR and multiple preset targets to be located. Based on time delay spoofing interference, time delay measurement error interference, and position error interference of the airborne platforms, a target echo mathematical model is constructed between the airborne platforms and the preset targets to be located. According to the target echo mathematical model, target echo signals corresponding to the multiple airborne platforms are obtained. Backpropagation (BP) imaging is performed on the target echo signals corresponding to the multiple airborne platforms to obtain SAR images corresponding to each airborne platform, wherein each SAR image includes multiple preset targets to be located. Based on the multiple SAR images and a preset TOA residual equation set, the target localization result of each preset target to be located is obtained by iteratively solving using the least squares method. This approach fully considers the impact of time delay measurement error interference and airborne platform position error interference on the target positioning results, while also taking into account the effect of time delay deception interference on the target positioning results. It can effectively avoid the problem that existing technologies, due to their failure to consider time delay deception interference, result in false targets with similar characteristics to the real target in the SAR images acquired by the airborne platform, thus affecting the target positioning accuracy and improving the accuracy of the target positioning results.

[0097] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0098] In one embodiment, such as Figure 4 As shown, a distributed airborne SAR target positioning device is provided, which is applied to a distributed airborne SAR system. The system includes: multiple airborne platforms equipped with SAR and multiple preset targets to be positioned, including: a target echo mathematical model construction module 10, a target echo signal acquisition module 11, multiple SAR image acquisition modules 12 and a target positioning result acquisition module 13.

[0099] Among them, the target echo mathematical model construction module 10 is used to construct a target echo mathematical model between the airborne platform and the preset target to be located based on the time delay deception interference, time delay measurement error interference and the position error interference of the airborne platform.

[0100] The target echo signal acquisition module 11 is used to acquire target echo signals corresponding to multiple airborne platforms according to the target echo mathematical model.

[0101] Multiple SAR image acquisition modules 12 are used to perform BP imaging on the target echo signals corresponding to multiple airborne platforms respectively, and acquire each SAR image corresponding to the multiple airborne platforms respectively, wherein each SAR image includes: multiple preset targets to be located.

[0102] The target localization result acquisition module 13 is used to obtain the target localization result of each preset target to be located by iteratively solving the least squares method based on multiple SAR images and the preset TOA residual equation set.

[0103] In the above embodiments, an application is made to a distributed airborne SAR system. The system includes multiple airborne platforms equipped with SAR and multiple preset targets to be located. A target echo mathematical model construction module constructs a target echo mathematical model between the airborne platforms and the preset targets based on time delay spoofing interference, time delay measurement error interference, and position error interference of the airborne platforms. A target echo signal acquisition module acquires the target echo signals corresponding to each of the multiple airborne platforms according to the target echo mathematical model. Multiple SAR image acquisition modules perform backpropagation (BP) imaging on the target echo signals corresponding to the multiple airborne platforms to acquire various SAR images corresponding to each airborne platform. Each SAR image includes multiple preset targets to be located. A target location result acquisition module iteratively solves the multiple SAR images and a preset TOA residual equation set using the least squares method to obtain the target location result for each preset target. This approach fully considers the impact of time delay measurement error interference and airborne platform position error interference on the target positioning results, while also taking into account the effect of time delay deception interference on the target positioning results. It can effectively avoid the problem that existing technologies, due to their failure to consider time delay deception interference, result in false targets with similar characteristics to the real target in the SAR images acquired by the airborne platform, thus affecting the target positioning accuracy and improving the accuracy of the target positioning results.

[0104] Specific limitations regarding the distributed airborne SAR target localization device can be found in the limitations of the distributed airborne SAR target localization method described above, and will not be repeated here. Each module in the aforementioned server can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independent of the processor in the computer device, or stored in software in the memory of the computer device, so that the processor can call and execute the corresponding operations of each module.

[0105] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static random access memory (SRAM) and dynamic random access memory (DRAM), etc.

[0106] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0107] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the scope of protection of the present invention. Therefore, the scope of protection of this invention should be determined by the appended claims.

Claims

1. A distributed airborne SAR target localization method, characterized in that, An application to a distributed airborne SAR system, the system comprising: multiple airborne platforms equipped with SAR and multiple preset targets to be located, the method comprising: Based on time delay spoofing interference, time delay measurement error interference, and airborne platform position error interference, a target echo mathematical model between the airborne platform and the preset target to be located is constructed. Based on the target echo mathematical model, target echo signals corresponding to multiple airborne platforms are obtained respectively; BP imaging is performed on the target echo signals corresponding to the multiple airborne platforms respectively to obtain SAR images corresponding to the multiple airborne platforms respectively, wherein each SAR image includes: multiple preset targets to be located; Based on multiple SAR images and a set of preset TOA residual equations, the target location results of each preset target to be located are obtained by iteratively solving the least squares method.

2. The method according to claim 1, characterized in that, The step of constructing a mathematical model of the target echo between the airborne platform and the preset target to be located, based on time delay spoofing interference, time delay measurement error interference, and position error interference of the airborne platform, includes: The time delay deception interference distance is determined based on the distance between the airborne platform and the preset target to be located, as well as the time delay deception interference signal of at least one deception interference source. The position error interference distance, including the time delay spoofing interference, is determined based on the error distance between the airborne platform and the preset target to be located and the time delay spoofing interference distance. Determine the interference distance of the time delay measurement error based on the interference of the time delay measurement error; The target echo mathematical model is constructed based on the position error interference distance and the time delay measurement error interference distance.

3. The method according to claim 2, characterized in that, The mathematical model of the target echo can be defined by the following expression: in, Indicates the first The amplitude of the target echo signal corresponding to each airborne platform The range window function represents the radar signal transmitted by the airborne platform. Indicates a fast time interval. Indicates the first The first moment The airborne platform and the first The position error interference distance between the preset targets to be located Indicates the first The first moment The airborne platform and the first The time delay measurement error interference distance between the preset targets to be located Let represent the azimuth window function of the radar signal transmitted by the airborne platform, and let c represent the speed of light. The wavelength corresponding to the center frequency of the radar signal. This indicates the frequency modulation (FM) of the radar signal.

4. The method according to claim 3, characterized in that, The time-delay spoofing interference distance can be defined by the following expression: in, Indicates the first The airborne platform and the first Between the first preset target to be located The time delay parameter of the interference signal, Indicates the first The first moment The airborne platform and the first The distance between preset targets to be located; The location error interference distance can be defined by the following expression: in, Indicates the first The first moment The airborne platform and the first Error distance between preset targets to be located; The time delay measurement error interference distance can be defined by the following expression: in, Indicates the first The first moment The airborne platform and the first The time delay measurement error between preset targets to be located.

5. The method according to claim 4, characterized in that, Before obtaining the target localization results for each preset target by iteratively solving the least squares method based on multiple SAR images and a preset TOA residual equation set, the method further includes: Construct the preset TOA residual equation set, which includes: multiple preset TOA residual equation subsets corresponding to the airborne platforms respectively, and each preset TOA residual equation subset includes: multiple preset TOA residual equations between each airborne platform and multiple preset targets to be located; The preset TOA residual equation set can be defined by the following expression: in, Indicates the first The actual coordinates of each airborne platform Indicates relative to the first The first airborne platform, based on the SAR image, acquired the first... The preset coordinates of the target to be located. Indicates the time at the center of the imaging The airborne platform mentioned above and the first The measured distance between the preset targets to be located.

6. The method according to claim 5, characterized in that, The preset target to be located is either a real target or a false target. The step involves iteratively solving the least squares method based on multiple SAR images and a preset TOA residual equation set to obtain the target location results for each preset target, including: For the SAR image, at least one real target to be located is determined from multiple preset targets to be located using the preset TOA residual equation set; For each real target to be located, a nonlinear positioning equation set is constructed based on the preset TOA residual equation set. Based on the aforementioned nonlinear positioning equations, the least squares method is used for iterative solution to obtain the target positioning results for each real target to be located.

7. The method according to claim 6, characterized in that, The step of determining at least one real target to be located from multiple preset targets to be located based on the SAR image using the preset TOA residual equation set includes: The SAR image is preprocessed, and the coordinate positions of each preset target to be located are obtained by two-parameter CFAR. For each of the airborne platforms, the measured distance between each airborne platform and each of the preset targets to be located is obtained based on the single-pulse echo signal of the airborne platform at the imaging center time. Based on the measured distance, the coordinate position, and the preset TOA residual equations, calculate the distance residual between the airborne platform and the preset target to be located; When the distance residuals between multiple airborne platforms and the same preset target to be located are all less than a preset threshold, the current preset target to be located is determined to be the real target to be located.

8. The method according to claim 7, characterized in that, For each real target to be located, a nonlinear positioning equation set is constructed based on the preset TOA residual equation set, including: For each real target to be located, the target preset TOA residual equation corresponding to each real target to be located is determined in the multiple preset TOA residual equation subgroups respectively; Based on multiple target preset TOA residual equations, a set of nonlinear positioning equations is constructed for each real target to be located.

9. The method according to claim 8, characterized in that, The step of iteratively solving the nonlinear positioning equations using the least squares method to obtain the target positioning results for each real target to be located includes: For each real target to be located, a target preset TOA residual equation is used to determine the initial target position of the real target to be located. Then, a Taylor expansion is performed on the target preset TOA residual equation at the initial target position to determine the pseudo-linear positioning equation. Based on multiple pseudo-linear positioning equations, construct a set of pseudo-linear positioning equations and obtain the matrix equations of the set of pseudo-linear positioning equations. The matrix equation is solved iteratively using the least squares method to obtain the target localization results for each real target to be located.

10. A distributed airborne SAR target positioning device, characterized in that, An application to a distributed airborne SAR system, the system comprising: multiple airborne platforms equipped with SAR and multiple preset targets to be located, the device comprising: The target echo mathematical model construction module is used to construct a target echo mathematical model between the airborne platform and the preset target to be located based on time delay deception interference, time delay measurement error interference and airborne platform position error interference. The target echo signal acquisition module is used to acquire target echo signals corresponding to multiple airborne platforms respectively, based on the target echo mathematical model. Multiple SAR image acquisition modules are used to perform BP imaging on the target echo signals corresponding to the multiple airborne platforms respectively, and acquire each SAR image corresponding to the multiple airborne platforms respectively, wherein each SAR image includes: multiple preset targets to be located; The target localization result acquisition module is used to obtain the target localization result of each preset target to be located by iteratively solving the least squares method based on multiple SAR images and a preset TOA residual equation set.

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