Method and device for suppressing coupled signals of ground-based SAR

Abstract

The present invention discloses a method and device for suppressing coupled signals of a ground-based SAR. The method comprises: collecting ground-based SAR echo signals; performing RVP correction processing on the ground-based SAR echo signals to obtain range-frequency-azimuth-time-domain signals; determining a range-Doppler domain signal based on the range-frequency-azimuth-time-domain signals; performing RPCA matrix decomposition on the range-Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix; performing correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient; and suppressing coupled signals of the ground-based SAR based on the optimal regularization coefficient. The present invention can effectively suppress coupled signals of the ground-based SAR and improve accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of ground-based SAR imaging, and in particular to a method and device for suppressing coupled signals of a ground-based SAR. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. No statement herein is admitted to be prior art by virtue of its inclusion in this section.

[0003] Ground-based synthetic aperture radar (GBSAR), also known as ground-based SAR, is a high-resolution microwave remote sensing device with all-day, all-weather, and high-resolution capabilities. It performs non-contact, continuous, fixed-point scanning of the observation scene, producing time-series images of the same observation area. Phase difference analysis of the time-series images allows for inversion of the deformation of each pixel in the scene image. With its advantages of non-contact, large-area, fixed-point, continuous observation and extremely high deformation inversion accuracy, GBSAR has broad applications in areas such as geological disaster early warning and mine landslide monitoring.

[0004] Ground-based SAR (SAR) is designed for long-term, fixed-point, continuous monitoring. To prevent the effects of the open air environment on ground-based SAR radar equipment, the radar equipment must be placed inside a monitoring station, with the antenna transmitting and receiving signals through a wave-transparent cover. Because radar signals are more susceptible to multipath effects, compared to open air environments, received echoes are more susceptible to interference from strong multipath reflections at close range in enclosed spaces, as well as coupling signals caused by insufficient isolation between the transmitter and receiver. This can create interference signals during later imaging. Coupling signals caused by insufficient isolation between receivers do not vary with slow time and can be removed using slow-time averaging. However, strong signals from close-range reflections vary with slow time, making them difficult to remove using slow-time averaging.

[0005] Existing techniques use principal component analysis (PCA) and SVD decomposition to extract coupling signals with a certain degree of time-varying properties in slow time. The PCA method assumes that all signals other than the coupling signal have a Gaussian distribution. However, actual scene signals other than the coupling signal typically do not conform to Gaussian distribution characteristics, resulting in significant errors in coupling signal extraction.

[0006] Therefore, there is an urgent need for a coupled signal suppression solution for ground-based SAR that can overcome the above problems. Summary of the Invention

[0007] An embodiment of the present invention provides a method for suppressing coupled signals of a ground-based SAR, which is used to effectively suppress coupled signals of the ground-based SAR and improve accuracy. The method includes:

[0008] Collect ground-based SAR echo signals;

[0009] Performing RVP correction processing on the ground-based SAR echo signal to obtain range-frequency-domain, azimuth-time-domain signals;

[0010] Determine a range-Doppler domain signal based on the range-frequency-domain-azimuth-time-domain signal;

[0011] Performing RPCA matrix decomposition on the range Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix;

[0012] Performing correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient;

[0013] The coupled signal of the ground-based SAR is suppressed according to the optimal regularization coefficient.

[0014] An embodiment of the present invention provides a coupled signal suppression device for a ground-based SAR, which is used to effectively suppress coupled signals of the ground-based SAR and improve accuracy. The device includes:

[0015] Echo signal acquisition module, used to collect ground-based SAR echo signals;

[0016] An RVP correction processing module is used to perform RVP correction processing on the ground-based SAR echo signal to obtain range-frequency-domain and azimuth-time-domain signals;

[0017] a range-Doppler domain signal determination module, configured to determine a range-Doppler domain signal based on the range-frequency-domain, azimuth-time-domain signals;

[0018] An RPCA matrix decomposition module is used to perform RPCA matrix decomposition on the range Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix;

[0019] An optimal regularization coefficient determination module, configured to perform correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient;

[0020] The coupled signal suppression module is used to suppress the coupled signal of the ground-based SAR according to the optimal regularization coefficient.

[0021] An embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for suppressing coupled signals of a ground-based SAR when executing the computer program.

[0022] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the coupling signal suppression method for the ground-based SAR is implemented.

[0023] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the coupled signal suppression method for the ground-based SAR is implemented.

[0024] Compared with the technical solution in the prior art that uses principal component analysis (PCA) to decompose coupled signals with certain time-varying properties in slow time through SVD decomposition, the embodiment of the present invention collects ground-based SAR echo signals; performs RVP correction processing on the ground-based SAR echo signals to obtain range-frequency-azimuth-time-domain signals; determines a range-Doppler domain signal based on the range-frequency-azimuth-time-domain signals; performs RPCA matrix decomposition on the range-Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix; performs correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient; and performs coupling signal suppression of the ground-based SAR based on the optimal regularization coefficient. The embodiment of the present invention transforms the ground-based SAR echo signal into the range Doppler domain, and then uses RPCA to decompose the range Doppler domain signal into two parts: a sparse scene matrix and a low-rank coupling matrix. The close-range strong reflection coupling signal appears as a bright line distributed along the range direction and has low rank. The scene echo has been preliminarily focused in this domain due to the principle of beam sharpening, meeting the sparsity requirement. Therefore, correlation analysis is performed on the sparse scene matrix and the low-rank coupling matrix to obtain the optimal regularization coefficient, avoiding the dependence of parameter selection on empirical values and effectively improving the accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0026] Figure 1 Schematic diagram of a coupled signal suppression method for a ground-based SAR according to an embodiment of the present invention;

[0027] Figure 2 Schematic diagram of the geometric model of the ground-based SAR in an embodiment of the present invention;

[0028] Figures 3 to 5 Schematic diagram of another method for suppressing coupled signals of a ground-based SAR according to an embodiment of the present invention;

[0029] Figure 6 2 is a structural diagram of a coupled signal suppression device based on ground-based SAR in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0031] As mentioned above, the existing coupling suppression method PCA has a large deviation in the extraction of low-rank coupling signals. In the actual GBSAR coupling signal suppression, complex signals such as strong interference in actual scenes usually interfere with the coupling signal estimation, resulting in a large error in the decomposition of the coupling signal. In order to suppress the coupling signal of ground-based SAR and improve the accuracy, the embodiment of the present invention provides a coupling signal suppression method for ground-based SAR, such as Figure 1 As shown, the method may include:

[0032] Step 101: collecting ground-based SAR echo signals;

[0033] Step 102: Perform RVP correction processing on the ground-based SAR echo signal to obtain range, frequency, azimuth, and time domain signals;

[0034] Step 103: Determine a range-Doppler domain signal based on the range-frequency-domain-azimuth-time-domain signal;

[0035] Step 104: Perform RPCA matrix decomposition on the range Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix;

[0036] Step 105: performing correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient;

[0037] Step 106: Suppress the coupled signal of the ground-based SAR according to the optimal regularization coefficient.

[0038] Depend on Figure 1As shown, the embodiment of the present invention is compared with the technical solution in the prior art that uses the principal component analysis method PCA to decompose through SVD to obtain a coupling signal with a certain time-varying property in slow time. The method collects ground-based SAR echo signals; performs RVP correction processing on the ground-based SAR echo signals to obtain range-frequency-azimuth-time-domain signals; determines the range-Doppler domain signal based on the range-frequency-azimuth-time-domain signals; performs RPCA matrix decomposition on the range-Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix; performs correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine the optimal regularization coefficient; and performs coupling signal suppression of the ground-based SAR based on the optimal regularization coefficient. The embodiment of the present invention transforms the ground-based SAR echo signal into the range Doppler domain, and then uses RPCA to decompose the range Doppler domain signal into two parts: a sparse scene matrix and a low-rank coupling matrix. The close-range strong reflection coupling signal appears as a bright line distributed along the range direction and has low rank. The scene echo has been preliminarily focused in this domain due to the principle of beam sharpening, meeting the sparsity requirement. Therefore, correlation analysis is performed on the sparse scene matrix and the low-rank coupling matrix to obtain the optimal regularization coefficient, avoiding the dependence of parameter selection on empirical values and effectively improving the accuracy.

[0039] The inventors discovered that RPCA takes into account the non-Gaussian distribution of other signals and, compared to PCA, incorporates sparsity regularization. Robust principal component analysis (RPCA) has already been applied to image denoising. Therefore, this paper attempts to apply this algorithm to signal denoising, proposing a method for suppressing coupled signals in the range-Doppler domain using robust principal component analysis (RPCA). The RPCA method is capable of decomposing both low-rank and sparse signals. In the range-Doppler domain, this paper utilizes RPCA to decompose the signal into two components: a low-rank matrix and a sparse matrix. Strongly reflected coupled signals at close range appear as bright lines distributed along the range axis, exhibiting low rank properties. Scene echoes are initially focused in this domain due to the principle of beam sharpening, thus meeting the sparsity requirement. Secondly, this project utilizes correlation analysis to optimize the regularization coefficient λ in the cost function for the RPCA optimization solution, avoiding reliance on empirical values for this parameter selection. In the range-Doppler domain, the sparse matrix obtained through RPCA decomposition represents the echo signal after coupled signal suppression, serving as the input signal for subsequent ground-based SAR imaging processing.

[0040] In step 101, ground-based SAR echo signals are collected.

[0041] Figure 2The figure is a schematic diagram of the geometric model of a ground-based SAR. The radar system moves at a constant speed on a straight track, with the antenna beam pointing to the area ahead. The radar transmits radar signals at regular intervals and receives echo signals reflected from the scene. A rectangular coordinate system is established with the center of the track as the coordinate origin O, the track motion direction as the x-axis, and the y-axis perpendicular to the track direction. The radar platform moves at a speed v along the positive direction of the x-axis, and the track length is L. P is an arbitrary point target in the scene, R0 is the distance from the point target P to the coordinate origin, and θ p is the oblique angle of the origin relative to the point target P.

[0042] The radar transmission signal is a frequency modulated continuous wave signal, and the expression of the transmission signal is:

[0043] S t (τ)=exp(jπKτ 2 +j2πf c τ) (1)

[0044] Among them, f c is the center frequency of the transmitted signal, K is the modulation frequency, τ is the fast time, τ∈[0,T p ], T p is the frequency modulated continuous wave pulse width.

[0045] The point target P echo signal model received by the radar is:

[0046]

[0047] Where μ is the slow time, symbol * represents conjugate, σ is the complex reflection coefficient of target P, τ0 is the echo delay of point target P, which is a function of slow time μ, and its expression is:

[0048] τ0=2R p (μ) / C (3)

[0049] Where C is the speed of light, R p (μ) represents the distance from the point target P to the radar platform, and its expression is:

[0050]

[0051] Using the linear relationship between the frequency and time of the FMCW, let the frequency f be:

[0052] f=Kτ+f c (5)

[0053] Substituting equation (5) into equation (2), the echo signal of the point target P can be converted into:

[0054]

[0055] The ground-based radar echo signal S1 is the superposition of the echoes of all scattering centers in the scene, the direct wave coupling signal and the close-range strong scattering coupling signal.

[0056] In step 102, RVP correction processing is performed on the ground-based SAR echo signal to obtain range-frequency-azimuth-time-domain signals.

[0057] In one embodiment, Figure 3 As shown, the ground-based SAR echo signal is subjected to RVP correction processing to obtain range-frequency-azimuth-time-domain signals, including:

[0058] Step 301: Perform range-direction inverse Fourier transform on the ground-based SAR echo signal;

[0059] Step 302: Multiply the transformed result by a preset compensation function and then perform a range Fourier transform to obtain a range frequency domain and azimuth time domain signal.

[0060] In specific implementation, the echo signal S1 received in the (f, μ) domain is subjected to an inverse Fourier transform in the range direction and transformed into the (t, μ) domain, where t is the time corresponding to the frequency f. The transformed signal S1 is then multiplied by the compensation function. The preset compensation function is:

[0061] H(t)=exp(-jπKt 2 ) (7)

[0062] Then perform the distance Fourier transform to the (f,μ) domain.

[0063] After RVP correction, the signal of the point target P is:

[0064]

[0065] After RVP correction, the direct wave coupling signal is:

[0066] S co1 (f,μ)≈Aexp{-j2πf·t0} (9)

[0067] Where t0 is the coupling signal delay from the transmitter to the receiver, and A is the complex scattering coefficient of the direct wave coupling signal.

[0068] After RVP correction, the close-range strong scattering coupling signal is:

[0069]

[0070] The serial number i is the number of the close-range strong scattering coupling signal, and N is the number of close-range strong scattering points. i (τ) is the distance between the radar and the close-coupled signal.

[0071] In step 103, a range-Doppler domain signal is determined based on the range-frequency-domain and azimuth-time-domain signals.

[0072] In one embodiment, determining a range-Doppler domain signal based on the range-frequency-azimuth-time domain signal includes:

[0073] Performing range inverse Fourier transform and azimuth Fourier transform on the range frequency domain and azimuth time domain signals to obtain range Doppler domain signals.

[0074] In practice, the RVP-corrected signal S2 undergoes an inverse Fourier transform in both range and azimuth to obtain the range-Doppler domain signal S3. A two-dimensional inverse Fourier transform is performed on the RVP-corrected echo signal to obtain the range-Doppler domain signal. The range-Doppler domain signal for a point target P is expressed as follows:

[0075]

[0076] Among them, f d is the Doppler frequency.

[0077] The direct wave coupling signal in the range Doppler domain is:

[0078]

[0079] The close-range strong scattering coupling signal in the range Doppler domain is:

[0080]

[0081] Among them, r i is the distance from the i-th close-range strong scattering point to the origin, θ i is the oblique angle of the origin relative to the i-th close-range strong scattering point.

[0082] In step 104, RPCA matrix decomposition is performed on the range Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix.

[0083] In one embodiment, performing RPCA matrix decomposition on the range-Doppler domain signal according to the following constraints includes:

[0084] min||A|| * +λ||E||1,stD=A+E (14)

[0085] Among them, A is the low-rank coupling matrix to be solved, E is the sparse scene matrix to be solved, D is the range Doppler domain signal S3 to be decomposed, and λ is the regularization coefficient.

[0086] In specific implementation, the range Doppler domain signal S3 is decomposed by RPCA matrix to obtain a sparse matrix E and a low-rank matrix A. The range Doppler domain signal S3 is decomposed by RPCA. In this domain, the coupled signal satisfies the low-rank characteristic and the scene echo satisfies the sparse characteristic. The collected range Doppler signal S3 is decomposed according to the above constraints. Usually, a set of different values of λ are taken (the range is 0.5-1.5, and the interval is 0.1), and a set of low-rank matrices A are obtained through RPCA decomposition. λ and the sparse matrix E λ Formula (14) is generally solved iteratively using the Lagrangian optimization algorithm.

[0087] In step 105, correlation analysis is performed on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient.

[0088] In one embodiment, Figure 4 As shown, correlation analysis is performed on the sparse scene matrix and the low-rank coupling matrix to determine the optimal regularization coefficient, including:

[0089] Step 401: Calculate the correlation coefficient between the sparse scene matrix and the low-rank coupling matrix;

[0090] Step 402: Take the minimum value of the correlation coefficients as the optimal regularization coefficient.

[0091] In specific implementation, the optimal λ is solved based on the correlation coefficient. λ and E λ The matrix is processed and the correlation coefficient ρ is obtained.

[0092]

[0093] The λ corresponding to the minimum correlation coefficient ρ is the optimal value. are the mean matrices of sparse and low-rank matrices respectively. The minimum correlation coefficient is taken as the optimal regularization coefficient according to the following formula

[0094]

[0095] In step 106, coupled signal suppression of the ground-based SAR is performed according to the optimal regularization coefficient.

[0096] In one embodiment, Figure 5 As shown, according to the optimal regularization coefficient, coupling signal suppression of the ground-based SAR is performed, including:

[0097] Step 501: Using the sparse scene matrix corresponding to the optimal regularization coefficient as the range Doppler domain signal after coupling signal suppression;

[0098] Step 502: Perform range Fourier transform and azimuth inverse Fourier transform on the range Doppler domain signal after the coupling signal is suppressed.

[0099] Step 503: Perform ground-based SAR imaging on the transformed result using back-projection BP or frequency domain imaging algorithm.

[0100] In specific implementation, the optimal regularization coefficient Corresponding E λ The sparse matrix serves as the range-Doppler domain signal S4 after coupling signal suppression. This signal is then subjected to a range Fourier transform and an inverse Fourier transform in the azimuth direction to obtain a coupling signal-suppressed (f, μ) domain signal S5. Backprojection (BP) or a frequency-domain imaging algorithm is then used on this (f, μ) domain signal S5 to obtain a ground-based radar image S free of coupling signal interference.

[0101] Compared to traditional PCA-based coupled signal suppression methods, the RPCA-based coupled signal suppression method in this embodiment of the present invention is more effective in removing interference signals, especially the impact of strong close-range scattered signals on imaging quality that PCA cannot remove. The optimal regularization parameter selection based on the correlation coefficient enables the RPCA algorithm parameters to adapt to the optimal suppression signal within the acquisition range.

[0102] Based on the same inventive concept, embodiments of the present invention also provide a coupled signal suppression device for a ground-based SAR, as described in the following embodiments. Since the principles underlying these solutions are similar to those of the coupled signal suppression method for a ground-based SAR, the implementation of the coupled signal suppression device for a ground-based SAR can be referenced to the implementation of the method, and any repetitions will not be repeated.

[0103] Figure 6 FIG. 1 is a structural diagram of a coupled signal suppression device for a ground-based SAR according to an embodiment of the present invention. Figure 6 As shown, the coupled signal suppression device of the ground-based SAR includes:

[0104] The echo signal acquisition module 601 is used to acquire ground-based SAR echo signals;

[0105] An RVP correction processing module 602 is configured to perform RVP correction processing on the ground-based SAR echo signal to obtain range-frequency-azimuth-time domain signals;

[0106] a range-Doppler domain signal determination module 603, configured to determine a range-Doppler domain signal based on the range-frequency-domain, azimuth-time-domain signals;

[0107] An RPCA matrix decomposition module 604 is configured to perform RPCA matrix decomposition on the range Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix;

[0108] An optimal regularization coefficient determination module 605 is configured to perform correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient;

[0109] The coupled signal suppression module 606 is configured to suppress the coupled signal of the ground-based SAR according to the optimal regularization coefficient.

[0110] Based on the aforementioned inventive concept, an embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the aforementioned method for suppressing coupled signals of a ground-based SAR when executing the computer program.

[0111] Based on the aforementioned inventive concept, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the coupled signal suppression method for the ground-based SAR is implemented.

[0112] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the coupled signal suppression method for the ground-based SAR is implemented.

[0113] Compared with the technical solution in the prior art that uses principal component analysis (PCA) to decompose coupled signals with certain time-varying properties in slow time through SVD decomposition, the embodiment of the present invention collects ground-based SAR echo signals; performs RVP correction processing on the ground-based SAR echo signals to obtain range-frequency-azimuth-time-domain signals; determines a range-Doppler domain signal based on the range-frequency-azimuth-time-domain signals; performs RPCA matrix decomposition on the range-Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix; performs correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient; and performs coupling signal suppression of the ground-based SAR based on the optimal regularization coefficient. The embodiment of the present invention transforms the ground-based SAR echo signal into the range Doppler domain, and then uses RPCA to decompose the range Doppler domain signal into two parts: a sparse scene matrix and a low-rank coupling matrix. The close-range strong reflection coupling signal appears as a bright line distributed along the range direction and has low rank. The scene echo has been preliminarily focused in this domain due to the principle of beam sharpening, meeting the sparsity requirement. Therefore, correlation analysis is performed on the sparse scene matrix and the low-rank coupling matrix to obtain the optimal regularization coefficient, avoiding the dependence of parameter selection on empirical values and effectively improving the accuracy.

[0114] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0115] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0116] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0117] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0118] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for suppressing coupled signals of a ground-based SAR, characterized in that: include: Collect ground-based SAR echo signals; Performing RVP correction processing on the ground-based SAR echo signal to obtain range-frequency-domain, azimuth-time-domain signals; Determine a range-Doppler domain signal based on the range-frequency-domain-azimuth-time-domain signal; Performing RPCA matrix decomposition on the range Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix; Performing correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient; The coupled signal of the ground-based SAR is suppressed according to the optimal regularization coefficient.

2. The coupled signal suppression method for ground-based SAR according to claim 1, wherein: Performing RVP correction processing on the ground-based SAR echo signal to obtain range-frequency-domain-azimuth-time-domain signals includes: Performing a range-direction inverse Fourier transform on the ground-based SAR echo signal; The transformed result is multiplied by the preset compensation function and then Fourier transformed in the range direction to obtain the range frequency domain and azimuth time domain signals.

3. The coupled signal suppression method for ground-based SAR according to claim 1, wherein: Determining a range-Doppler domain signal according to the range-frequency-domain-azimuth-time-domain signal includes: Performing range inverse Fourier transform and azimuth Fourier transform on the range frequency domain and azimuth time domain signals to obtain range Doppler domain signals.

4. The coupled signal suppression method for ground-based SAR according to claim 1, wherein: Performing RPCA matrix decomposition on the range-Doppler domain signal according to the following constraints, including: min||A|| * +λ||E||1,stD=A+E Among them, A is the low-rank coupling matrix to be solved, E is the sparse scene matrix to be solved, D is the range Doppler domain signal S3 to be decomposed, and λ is the regularization coefficient.

5. The coupled signal suppression method for ground-based SAR according to claim 1, wherein: Performing correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine the optimal regularization coefficient includes: Calculating a correlation coefficient between the sparse scene matrix and the low-rank coupling matrix; The minimum value among the correlation coefficients is taken as the optimal regularization coefficient.

6. The coupled signal suppression method for ground-based SAR according to claim 1, wherein: According to the optimal regularization coefficient, coupled signal suppression of the ground-based SAR is performed, including: Using the sparse scene matrix corresponding to the optimal regularization coefficient as the range Doppler domain signal after coupling signal suppression; Performing range Fourier transform and azimuth inverse Fourier transform on the range Doppler domain signal after coupling signal suppression; The transformed results are used for ground-based SAR imaging using back-projection BP or frequency domain imaging algorithms.

7. A coupling signal suppression device for ground-based SAR, characterized in that: include: Echo signal acquisition module, used to collect ground-based SAR echo signals; An RVP correction processing module is used to perform RVP correction processing on the ground-based SAR echo signal to obtain range-frequency-domain and azimuth-time-domain signals; a range-Doppler domain signal determination module, configured to determine a range-Doppler domain signal based on the range-frequency-domain, azimuth-time-domain signals; An RPCA matrix decomposition module is used to perform RPCA matrix decomposition on the range Doppler domain signal to obtain a sparse scene matrix and a low-rank coupling matrix; An optimal regularization coefficient determination module, configured to perform correlation analysis on the sparse scene matrix and the low-rank coupling matrix to determine an optimal regularization coefficient; The coupled signal suppression module is used to suppress the coupled signal of the ground-based SAR according to the optimal regularization coefficient.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

Images