SAR sparse imaging method, device, electronic device and storage medium for moving targets

Abstract

The embodiment of the present invention discloses a moving target SAR sparse imaging method, device, electronic device and storage medium. The method comprises: performing clutter suppression processing on the echo signal of the collected moving target linear frequency modulation signal, then using a spectrum analysis method and performing motion compensation on the radar and the moving target based on the clutter-suppressed echo signal to obtain a motion-compensated echo signal, then constructing a parameterized characterization dictionary based on the motion-compensated echo signal and representing the motion-compensated echo signal according to the parameterized characterization dictionary, and using this as a constraint condition to construct an objective function of sparse aperture imaging and parameter estimation, finally using an orthogonal matching pursuit method to solve the objective function, and performing Doppler ambiguity number estimation and phase error correction on the moving target, so as to obtain a SAR image of the moving target with a large response dynamic range and good focusing performance.

Description

Technical Field

[0001] The embodiment of the present invention relates to a synthetic aperture radar (SAR) sparse imaging method, and more specifically, to a SAR sparse imaging method for a moving target. Background Art

[0002] Synthetic Aperture Radar (SAR) is a modern active remote sensing sensor that can provide high-resolution images of observed scenes. In recent years, it has been known from the theory of compressed sensing (CS) that the signal can be accurately reconstructed from the downsampled data with a high probability by using sparse optimization technology, thus breaking through the limitation of Nyquist sampling. Accordingly, compressed sensing has been widely used in SAR imaging, and one of its important applications is to reduce the sampling data, such as sparse aperture imaging. For SAR Ground Moving Target Imaging (SAR-GMTIm), motion compensation is an important issue that determines the imaging performance of moving targets. In addition to the movement of the radar platform, there is also additional movement of the moving target, which introduces range unit migration and high-order phase modulation to the echo data (the azimuth unit also has migration). After SAR focused imaging, the moving targets in the image often have two-dimensional cross-unit migration problems in range and azimuth, which manifests as two-dimensional "defocusing". Under sparse aperture, SAR moving target imaging is more complicated. Therefore, it is necessary to study sparse aperture SAR moving target imaging and compensation refocusing algorithms to ensure better imaging performance. Summary of the invention

[0003] The purpose of the present invention is to overcome the above-mentioned technical problems and, for sparse aperture moving target imaging, propose a SAR sparse imaging method, device, electronic device and storage medium for moving targets, which can suppress the problems of defocus, blur and misalignment of images caused by moving targets, thereby realizing a synthetic aperture radar image of the moving target without blur.

[0004] The embodiment of the present invention provides a SAR sparse imaging method for a moving target, comprising the following steps:

[0005] Step S1, collecting an echo signal of a linear frequency modulation signal emitted by a synthetic aperture radar moving along a predetermined trajectory at a preset speed to a moving target;

[0006] Step S2, performing stationary clutter suppression processing on the echo signal of the linear frequency modulation signal to obtain an echo signal after clutter suppression;

[0007] Step S3, using a spectrum analysis method and performing motion compensation on the radar and the moving target based on the echo signal after clutter suppression to obtain a motion compensated echo signal;

[0008] Step S4, constructing a parameterized characterization dictionary based on the motion-compensated echo signal and representing the motion-compensated echo signal according to the parameterized characterization dictionary;

[0009] Step S5, constructing an objective function of sparse aperture imaging and parameter estimation by taking the motion-compensated echo signal represented by the parameterized characterization dictionary as a constraint condition;

[0010] Step S6, using an orthogonal matching pursuit method to solve the objective function, and performing Doppler ambiguity number estimation and phase error correction on the moving target to obtain a SAR image of the moving target.

[0011] Correspondingly, an embodiment of the present invention further provides a SAR sparse imaging device for a moving target, comprising: a data acquisition module, a clutter suppression module, a compensation module, a post-processing module and an imaging module.

[0012] The data acquisition module is used to collect the echo signal of the linear frequency modulation signal emitted by the synthetic aperture radar moving along a predetermined trajectory at a preset speed to the moving target;

[0013] The clutter suppression module is used to perform stationary clutter suppression processing on the echo signal of the linear frequency modulation signal to obtain an echo signal after clutter suppression;

[0014] The compensation module is used to perform motion compensation on the radar and the moving target based on the echo signal after clutter suppression using a spectrum analysis method to obtain a motion-compensated echo signal;

[0015] The post-processing module is used to construct a parameterized characterization dictionary based on the motion-compensated echo signal and represent the motion-compensated echo signal according to the parameterized characterization dictionary, and then construct an objective function of sparse aperture imaging and parameter estimation using the motion-compensated echo signal represented by the parameterized characterization dictionary as a constraint condition;

[0016] The imaging module is used to solve the objective function by adopting an orthogonal matching pursuit method, and to perform Doppler fuzzy number estimation and phase error correction on the moving target to obtain a SAR image of the moving target.

[0017] Correspondingly, an embodiment of the present invention further provides an electronic device, comprising a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute the steps in SAR sparse imaging of moving targets described in any of the above embodiments.

[0018] In addition, an embodiment of the present invention further provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the SAR sparse imaging of moving targets described in any of the above embodiments are implemented.

[0019] The embodiment of the present invention adopts clutter suppression processing on the echo signal of the linear frequency modulation signal of the collected moving target, and then uses a spectrum analysis method to perform motion compensation on the radar and the moving target based on the echo signal after clutter suppression to obtain a motion-compensated echo signal, and then constructs a parameterized characterization dictionary based on the motion-compensated echo signal and represents the motion-compensated echo signal according to the parameterized characterization dictionary, and uses this as a constraint condition to construct an objective function of sparse aperture imaging and parameter estimation, and finally adopts an orthogonal matching pursuit method to solve the objective function, and performs Doppler ambiguity number estimation and phase error correction on the moving target, so as to obtain a SAR image of the moving target with a large response dynamic range and good focusing performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. 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.

[0021] Figure 1 is a flow chart of a SAR imaging method for a moving target provided by an embodiment of the present invention;

[0022] Figure 2 A schematic diagram of a specific structure for constructing a SAR imaging geometric structure is provided in an embodiment of the present invention;

[0023] Figure 3 is a simulation experiment result diagram of an embodiment of the present invention;

[0024] Figure 4 It is a two-dimensional imaging effect diagram of measured data of an embodiment of the present invention;

[0025] Figure 5 is a sparsely reconstructed image according to an embodiment of the present invention;

[0026] Figure 6is a simulation experiment result diagram of an embodiment of the present invention;

[0027] Figure 7 A schematic structural diagram of a single-channel synthetic aperture radar imaging device provided by an embodiment of the present invention;

[0028] Figure 8 It is a schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0030] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein.

[0031] In view of the problem that moving targets in the prior art are often blurred in the SAR image domain, the present invention provides a SAR sparse imaging method for moving targets. The motion compensation process provided by the present invention is roughly divided into two steps: first, spectrum analysis processing is performed in the range-frequency and azimuth-time domains, and then residual component correction is performed in sparse imaging. In view of the Doppler blur and phase error problems of moving targets, a moving target parameter sparse imaging method is proposed. In this method, a parameterized characterization dictionary is used to solve the above two key problems. On this basis, an improved orthogonal matching pursuit (OMP) method is used to estimate the Doppler blur number and correct the phase error of the moving target to achieve high-quality imaging. At the same time, the method provided by the present invention can handle the situation of multiple moving targets, thereby obtaining a multi-moving target SAR image with a large response dynamic range and good focusing performance.

[0032] Combine the following Figure 1-Figure 8 The present invention describes a SAR sparse imaging method, device, electronic device and storage medium for a moving target according to an embodiment of the present invention.

[0033] Figure 1 FIG. 1 is a flow chart of a SAR imaging method for a moving target provided by an embodiment of the present invention. Figure 1 A SAR imaging method for a moving target, comprising:

[0034] Step S1, collecting an echo signal of a linear frequency modulation signal emitted by a synthetic aperture radar moving along a predetermined trajectory at a preset speed to a moving target;

[0035] Step S2, performing stationary clutter suppression processing on the echo signal of the linear frequency modulation signal to obtain an echo signal after clutter suppression;

[0036] Step S3, using a spectrum analysis method and performing motion compensation on the radar and the moving target based on the echo signal after clutter suppression to obtain a motion compensated echo signal;

[0037] Step S4, constructing a parameterized characterization dictionary based on the motion-compensated echo signal and representing the motion-compensated echo signal according to the parameterized characterization dictionary;

[0038] Step S5, constructing an objective function of sparse aperture imaging and parameter estimation by taking the motion-compensated echo signal represented by the parameterized characterization dictionary as a constraint condition;

[0039] Step S6, using an orthogonal matching pursuit method to solve the objective function, and performing Doppler ambiguity number estimation and phase error correction on the moving target to obtain a SAR image of the moving target.

[0040] The technical solution provided by the embodiment of the present invention has the following advantages compared with the prior art:

[0041] Most sparse SAR imaging algorithms in the prior art only consider the motion of the radar platform, while ignoring the motion of the moving target. At the same time, most sparse SAR moving target imaging methods only consider the azimuth unit motion introduced by the moving target, but do not consider the existence of the range unit motion. The embodiment of the present invention utilizes a parameterized sparse method to achieve two-dimensional unit motion correction under a sparse aperture, thereby ensuring high-quality imaging of the moving target.

[0042] The above steps S1 to S6 are described in detail below.

[0043] Figure 2 FIG. 1 is a schematic diagram of a specific structure for constructing a SAR imaging geometric structure provided by an embodiment of the present invention. Figure 2 As shown, in the above step S1, the echo signal of the linear frequency modulation signal emitted by the synthetic aperture radar moving along a predetermined trajectory at a preset speed to the moving target is collected. The predetermined trajectory movement is as follows: Figure 2 As shown in the flight path, the airborne radar flies along the predetermined trajectory at a speed v and transmits a linear frequency modulation (LFM) signal at a certain pulse repetition frequency. The collected echo signal can be expressed as:

[0044]

[0045] The moving direction of the radar is defined as the x-axis, and the direction perpendicular to the moving direction of the radar is defined as the y-axis. p ,y p ) with speed (v x ,v y ) Exercise, R p =R0+y p is the time t between the radar and the moving target P in azimuth a The instantaneous distance, V is the radar speed,

[0046] In the above step S2, the echo signal is processed using a shifted phase center antenna to obtain the echo signal after clutter suppression, wherein the echo signal after clutter suppression is obtained via the following formula:

[0047]

[0048] Among them, σ p is the back reflection coefficient of the moving target P, W r (·) is the distance frequency domain f r The window function, W a (·) represents the azimuth time domain t a The window function of is the central time of observing the moving target P, f c is the carrier frequency of the transmitted signal, and c is the propagation speed of the electromagnetic wave.

[0049] In the above step S3, a spectrum analysis reference function is constructed according to the following formula:

[0050]

[0051] The clutter-suppressed echo signal is multiplied by the spectrum analysis reference function to obtain the motion-compensated echo signal obtained by the following formula:

[0052]

[0053] Specifically, the echo signal after clutter suppression by the DPCA is multiplied by the SPECAN reference function to achieve motion compensation for the radar and the moving target.

[0054] The above step S4 specifically includes:

[0055] In the first step, a compressed random sampling method is used to obtain a compressed sampling matrix of sparse aperture;

[0056] The second step is to construct a parameterized characterization dictionary of motion modulation of the moving target based on the motion compensated echo signal;

[0057] The third step is to divide the parameterized characterization dictionary into two parts, representing linear MTRC (Migration Through Resolution Cell) and phase modulation respectively;

[0058] The fourth step is to rewrite the motion-compensated echo signal using the parameterized characterization dictionary to obtain:

[0059] s=ΦΨ(α,β)x+n, y=Ψ2(β)x, Ψ(α,β)=Ψ1(α)Ψ2(β);

[0060] Where s, x and n represent the echo signal, SAR image and system noise respectively, Φ is the compressed sampling matrix of sparse sampling, Ψ(α, β) is the parameterized representation dictionary of the velocity modulation of all moving targets represented by vectors α and β, and Ψ(α, β) is divided into two parts, Ψ1(α) and Ψ2(β), which represent linear MTRC and phase modulation respectively;

[0061] Among them, the expression of Ψ1(α) is:

[0062] Ψ1(α)=F a-mtrc (n amb )F r

[0063]

[0064]

[0065] In the above formula, F r represents the Fourier transform of the distance dimension, F a-mtrc (n amb ) is a function with a scaling factor f r The scaling transformation of the azimuth dimension, n amb is the unknown Doppler ambiguity number vector of all moving targets, determined by α; M and N are discrete numbers in the azimuth and distance dimensions respectively;

[0066] The detailed form of Ψ2(β) is:

[0067] Ψ2(β)=F a -1 C(β)⊙F a

[0068]

[0069]

[0070] in, is the Fourier transform or inverse Fourier transform, ⊙ is the Hadamard product, C(β)⊙F a Yes

[0071] It should be noted that the purpose of the above step S4 is to obtain a sparse aperture (SA) SAR image, wherein the spectrum analysis (SPECAN) imaging algorithm is an imaging algorithm widely used in SAR quick-view processing, and its main feature is to adopt -Deramp processing in azimuth direction, with small amount of calculation.

[0072] In the above step S5, the objective function of the sparse aperture imaging and parameter estimation is constructed according to the following formula. The objective function expression is:

[0073]

[0074] where ·0 is the L0-norm of the vector.

[0075] In the above step S6, the step S6 includes:

[0076] In the first step, the moving target component is extracted by estimating and compensating the moving target, wherein the moving target component is extracted according to the following formula:

[0077]

[0078] in, is the estimated fuzzy number of the pth moving target, and is the number of distance and azimuth units of the pth moving target;

[0079] The second step is to estimate the phase error of the moving target component, wherein the phase error estimate is obtained according to the following formula:

[0080]

[0081] in, For and of The windowing result is is the estimated chirp signal of the pth moving target, and After updating by the above formula, the signal component of the moving target can be estimated as;

[0082]

[0083]

[0084]

[0085] in, is the estimate of the pth moving target;

[0086] Step 3: Calculate the residual component in the following way: Update the echo signal rewritten by the parameterized characterization dictionary in step S4 by subtracting the signal component of the moving target estimated in the first and second steps, and obtain the updated echo signal represented by the following formula:

[0087]

[0088] in, It is SAR image components, namely Subsequently, the echo signal is updated as The moving target number is updated to p=p+1;

[0089] Step 4: Iterative solution: Repeat steps 1 to 3 to continuously extract the next moving target by estimating parameters until all moving targets are extracted to obtain SAR images of all moving targets.

[0090] In order to illustrate the effectiveness of the present invention for motion compensation of sparse imaging of moving target synthetic aperture radar, the following is further demonstrated through simulation data and measured data experiments:

[0091] Based on the MATLAB software platform, the system parameters of the single-channel SAR simulation experiment are as follows:

[0092] SAR system simulation parameter setting

[0093] parameter value parameter value Radar center frequency 10GHz bandwidth 360MHz Sampling frequency 400MHz Scene center distance 20km Radar Pulse Repetition Frequency (PRF) 500Hz Radar platform movement speed 100m / s

[0094] The following is combined with Figure 3 The two-dimensional imaging effect of the simulation data of the present invention is further described.

[0095] Figure 3 : is a simulation experiment result diagram of an embodiment of the present invention, wherein: Figure 3 (a)- Figure 3 (c) The horizontal axis is the pulse number, and the vertical axis is the distance sampling unit. Figure 3 (d)- Figure 3 (f) The horizontal axis is the azimuth sampling unit, and the vertical axis is the distance sampling unit.

[0096] Figure 3(a) shows the range profile of the radar to show that there is a significant MTRC. The linear MTRC is mainly derived from the range velocity of the moving target, and the quadratic MTRC is mainly derived from the motion modulation of the radar platform. In order to compensate for the motion modulation in the envelope and phase terms, the spectrum analysis method proposed in step S3 is applied to motion compensate the radar and the moving target based on the clutter suppressed echo signal to obtain a motion compensated echo signal, and the processed radar range profile is as follows Figure 3 (b). Figure 3 As shown in (b), MTRC is in linear form after SPECAN processing. Then, using Keystone transform (which can compensate for range travel), we try to correct the residual linear MTRC and get Figure 3 (c) The results shown; Figure 3 As shown in (c), the range profile of the slow moving target has been successfully corrected. However, for the two moving targets with Doppler blur, there is still a large MTRC. Therefore, the azimuth Fourier transform is used to obtain the SAR image without phase error correction, as shown in Figure 3 (d) as shown.

[0097] For two fast-moving moving targets, there is obvious 2D blur. Therefore, it is necessary to perform motion compensation on the moving targets, including MTRC and phase error correction. In the case of full aperture, the moving target parameter sparse algorithm proposed in the embodiment of the present invention is used to focus the moving target image well, such as Figure 3 (e). For the sake of clarity, Figure 3 The dotted rectangular area in (e) is enlarged to Figure 3 (f) is shown. Figure 3 (e) and Figure 3 (f) It can be clearly seen that by overcoming the Doppler ambiguity of the radar and the moving target, MTRC correction and phase error correction can achieve perfect motion compensation for the moving target.

[0098] In order to illustrate the effectiveness of the embodiment of the present invention for SAR sparse imaging of moving targets, the echo signal of SAR sparse imaging of moving targets is further demonstrated by using the algorithm proposed in the embodiment of the present invention:

[0099] In order to verify the robustness of the algorithm, the following Figure 4 The two-dimensional imaging effect of the measured data of the embodiment of the present invention is further described.

[0100] For example, different degrees of complex random Gaussian noise are added to the acquired echo signal, and the signal-to-noise ratio of the noise is set to 20db, 10db and 5db respectively. In the simulation experiment, SA (Synthetic Aperture) data is used with half and one quarter of the full aperture, as shown in Figure 4 (a) and Figure 4 Then, using the traditional SAR imaging algorithm, azimuth focusing is performed in the azimuth dimension, and the processing results of the two data sets are as follows: Figure 4 (b) and Figure 4 (d) as shown.

[0101] like Figure 4 (b) and Figure 4 As shown in (d), there are too many artifacts (ghost images) in the image. The reasons are mainly two-fold: sparse data and potential residual MTRC and phase error modulation.

[0102] Under two sparse sampling conditions, simulation experiments were conducted on six data sets with signal-to-noise ratios of 20db, 10db, and 5db, respectively. The experimental results show that the algorithm provided by the embodiment of the present invention can overcome the influence of synthetic aperture and motion modulation at the same time. The sparsely reconstructed image obtained is as follows: Figure 5 As shown. Figure 5 As shown, the first line Figure 5 (a)- Figure 5 (b) is the result of using half pulses at full aperture, while the second row Figure 5 (d)- Figure 5 (f) is the result of using a quarter pulse of the full aperture. The experimental results show that the algorithm can obtain a well-focused image from the compressed sampling data, thanks to the process of combining sparse imaging with motion compensation.

[0103] In order to further verify the effectiveness of the algorithm, simulation experiments were carried out using the measured data of an airborne platform.

[0104] The radar has one transmitter and three receivers, operating in X-band with a signal bandwidth of 18 MHz and a pulse repetition frequency (PRF) of about 830 Hz. Here, 1024 pulses are used for SAR GMTIm with an azimuth resolution of about 6.0 m. After channel alignment and channel balancing, SAR focusing, including SPECAN processing and Keystone transform, is applied to obtain a coarsely focused SAR image, such as Figure 6 (a) shows that for most moving targets, there is 2D or at least azimuth ambiguity. Range ambiguity is due to the existence of MTRC caused by Doppler ambiguity. And azimuth ambiguity is caused by the phase error modulation of the moving target.

[0105] Therefore, it is necessary to perform residual MTRC correction and phase error correction on the well-focused SAR image. Then, based on the algorithm proposed in the embodiment of the present invention, the sparsely reconstructed image is as follows: Figure 6 (b) shows that the MTRC and phase errors are successfully removed. Next, the algorithm proposed in the embodiment of the present invention is applied to use the SA data for sparse imaging. Figure 6 (c) and 6f show the data with half a quarter full aperture used. Figure 6 (d) and Figure 6 (f) are the sparse reconstructed images in these two cases. The experimental results show that the algorithm can handle SA and motion compensation problems well, and can obtain high-quality SAR images even in the presence of Doppler ambiguity. This advantage is mainly due to the parameter sparse method proposed in the embodiment of the present invention. The above simulation experiments verify the effectiveness and feasibility of the method proposed in the embodiment of the present invention.

[0106] According to yet another aspect of the present invention, an embodiment of the present invention provides a moving target synthetic aperture radar sparse imaging device.

[0107] Figure 7 Schematic diagram of the structure of a single-channel synthetic aperture radar imaging device provided by an embodiment of the present invention. Figure 7 As shown, a synthetic aperture radar imaging device 1000 includes: a data acquisition module 1010, a clutter suppression module 1020, a compensation module 1030, a post-processing module 1040 and an imaging module 1050.

[0108] The data acquisition module 1010 is used to acquire the echo signal of the linear frequency modulation signal emitted by the synthetic aperture radar moving along a predetermined trajectory at a preset speed to the moving target.

[0109] The clutter suppression module 1020 is used to perform stationary clutter suppression processing on the echo signal of the linear frequency modulation signal to obtain a clutter-suppressed echo signal.

[0110] The compensation module 1030 is used to use a spectrum analysis method and perform motion compensation on the radar and the moving target based on the echo signal after clutter suppression to obtain a motion compensated echo signal.

[0111] The post-processing module 1040 is used to construct a parameterized characterization dictionary based on the motion-compensated echo signal and represent the motion-compensated echo signal according to the parameterized characterization dictionary, and then construct an objective function of sparse aperture imaging and parameter estimation using the motion-compensated echo signal represented by the parameterized characterization dictionary as a constraint condition.

[0112] The imaging module 1050 is used to solve the objective function by adopting an orthogonal matching pursuit method, and perform Doppler ambiguity number estimation and phase error correction on the moving target to obtain a SAR image of the moving target.

[0113] Among them, other aspects of the specific steps of the post-preprocessing module 1040 are the same or similar to the synthetic aperture radar sparse imaging method of moving targets described above, and are not repeated here.

[0114] Figure 8 is a schematic diagram of the physical structure of an electronic device provided by an embodiment of the present invention, such as Figure 8 As shown, the electronic device may include: a processor 1110, a communication interface 1120, a memory 1130 and a communication bus 1140, wherein the processor 1110, the communication interface 1120, and the memory 1130 communicate with each other through the communication bus 1140. The processor 1110 may call the logic instructions in the memory 1130 to execute the above-mentioned single-channel synthetic aperture radar sparse imaging method. Other aspects provided by this embodiment are the same or similar to the single-channel synthetic aperture radar sparse imaging method described above, and will not be repeated here.

[0115] In addition, the logic instructions in the above-mentioned memory 1130 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or wide disk and other media that can store program codes.

[0116] According to another aspect of the present invention, an embodiment of the present invention further provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, and when the program instructions are executed by a computer, the computer can execute the synthetic aperture radar sparse imaging method provided in the above embodiments. Other aspects provided by this embodiment are the same or similar to the synthetic aperture radar sparse imaging method for moving targets described above, and will not be repeated here.

[0117] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0118] To this end, according to another aspect of the present invention, an embodiment of the present invention further provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, the method for synthetic aperture radar sparse imaging of moving targets provided in the above embodiments is implemented. For example, the computer program may execute the following steps:

[0119] Step S1, collecting echo data of a linear frequency modulation signal emitted by a synthetic aperture radar flying along a predetermined route at a preset speed to a moving target;

[0120] Step S2, based on the echo data of the linear frequency modulation signal, under the condition of sparse aperture, adopting the shifted phase center antenna method to suppress the stationary clutter, and obtaining the echo data processed by the shifted phase center antenna;

[0121] Step S3, using the SPECAN method to perform motion compensation on the radar platform and the moving target to obtain echo data after SPECAN compensation;

[0122] Step S4, establishing a discrete sparse aperture signal model using a parameterized characterization dictionary to obtain a sparse aperture SAR image;

[0123] Step S5, using the SPECAN processing result represented by the parameterized characterization dictionary as a constraint condition, constructing an objective function of sparse aperture imaging and parameter estimation;

[0124] Step S6, using the orthogonal matching pursuit method to solve the objective function, and performing Doppler ambiguity number estimation and phase error correction on the objective function to obtain SAR images of all moving targets.

[0125] Other aspects provided by the embodiments of the present invention are the same or similar to the synthetic aperture radar sparse imaging method described above and will not be described in detail here.

[0126] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0127] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0128] Since the computer program stored in the storage medium can execute the steps in any one of the moving target synthetic aperture radar sparse imaging methods provided in the embodiments of the present invention, the beneficial effects that can be achieved by any one of the moving target synthetic aperture radar sparse imaging methods provided in the embodiments of the present invention can be achieved. For details, please refer to the previous embodiments and will not be repeated here.

[0129] The above is a detailed introduction to a moving target synthetic aperture radar sparse imaging method, device, electronic device and storage medium provided in an embodiment of the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A SAR sparse imaging method for a moving target, characterized in that: The following steps are involved: Step S1, collecting an echo signal of a linear frequency modulation signal emitted by a synthetic aperture radar moving along a predetermined trajectory at a preset speed to a moving target; Step S2, performing stationary clutter suppression processing on the echo signal of the linear frequency modulation signal to obtain an echo signal after clutter suppression; Step S3, using a spectrum analysis method and performing motion compensation on the radar and the moving target based on the echo signal after clutter suppression to obtain a motion compensated echo signal; Step S4, constructing a parameterized characterization dictionary based on the motion-compensated echo signal and representing the motion-compensated echo signal according to the parameterized characterization dictionary; Step S5, constructing an objective function of sparse aperture imaging and parameter estimation by taking the motion-compensated echo signal represented by the parameterized characterization dictionary as a constraint condition; Step S6, using an orthogonal matching pursuit method to solve the objective function, and performing Doppler ambiguity number estimation and phase error correction on the moving target to obtain a SAR image of the moving target; The echo signal obtained in step S1 is: ； The moving direction of the radar is defined as the x-axis, and the direction perpendicular to the radar movement is defined as the y-axis. At speed sports, For radar and moving targets P Azimuth time t a Time distance, V Radar movement speed, ; The step S2 comprises: using a shifted phase center antenna to process the echo signal to obtain the echo signal after clutter suppression, wherein the echo signal after clutter suppression is obtained via the following formula: in, Is a sports goal P The retroreflection coefficient, is the distance frequency domain f r function, Indicates the time domain of the direction t a The window function of Observe moving targets P The center time, f c Transmit signal carrier frequency, c The speed of electromagnetic wave propagation; The step S3 comprises: constructing a spectrum analysis reference function according to the following formula: The clutter-suppressed echo signal is multiplied by the spectrum analysis reference function to obtain the motion-compensated echo signal obtained by the following formula: ； The step S4 comprises: In the first step, a compressed random sampling method is used to obtain a compressed sampling matrix of sparse aperture; The second step is to construct a parameterized characterization dictionary of motion modulation of the moving target based on the motion compensated echo signal; The third step is to divide the parameterized characterization dictionary into two parts, representing linear MTRC and phase modulation respectively; The fourth step is to rewrite the motion-compensated echo signal using the parameterized characterization dictionary, and obtain the motion-compensated echo signal represented by the parameterized characterization dictionary according to the following formula: ； in, s , x and n They are respectively represented as echo signal, SAR System noise, is the compressed sampling matrix of sparse sampling, It is composed of vector and A parameterized dictionary representing the velocity modulation of all moving objects represented by Divided into and Two parts, representing linear MTRC and phase modulation; in, The expression is: In the above formula represents the Fourier transform of the distance dimension, is a scaling factor The scaling transformation of the azimuth dimension, is the unknown Doppler fuzzy number vector of all moving targets, given by Decide; and are discrete numbers in the dimensions of direction and distance respectively; The expression is: in, is the Fourier transform or inverse Fourier transform, It is Adamaj. is a chirped Fourier dictionary, is a constant scaling factor The discrete chirp rate of The step S5 comprises: constructing the objective function of the sparse aperture imaging and parameter estimation according to the following formula: ， ； in It is a vector -norm; The step S6 comprises: In the first step, the moving target component is extracted by estimating and compensating the moving target, wherein the moving target component is extracted according to the following formula: in, It is The estimated fuzzy number of moving targets, and It is The number of distance and azimuth units of a moving target; The second step is to estimate the phase error of the moving target component, wherein the phase error estimate is obtained according to the following formula: in, For and of The windowing result is It is Estimation of moving objects Signal; and After updating the above formula, the signal component of the moving target can be estimated as: in, It is Estimation of moving targets; Step 3: Calculate the residual component in the following way: Update the echo signal rewritten by the parameterized characterization dictionary in step S4 by subtracting the signal component of the moving target estimated in the first and second steps, and obtain the updated echo signal represented by the following formula: in, It is SAR image components, namely ; Subsequently, the echo signal is updated to , the moving target number is updated to ; Step 4: Iterative solution: Repeat steps 1 to 3 to continuously extract the next moving target by estimating parameters until all moving targets are extracted.

2. A SAR imaging device for a moving target, characterized in that: include: A data acquisition module, used for acquiring an echo signal of a linear frequency modulation signal emitted by a synthetic aperture radar moving along a predetermined trajectory at a preset speed to a moving target; A clutter suppression module, used for performing stationary clutter suppression processing on the echo signal of the linear frequency modulation signal to obtain an echo signal after clutter suppression; A compensation module, configured to perform motion compensation on the radar and the moving target based on the echo signal subjected to clutter suppression by using a spectrum analysis method, so as to obtain a motion-compensated echo signal; A post-processing module, configured to construct a parameterized characterization dictionary based on the motion-compensated echo signal and represent the motion-compensated echo signal according to the parameterized characterization dictionary, and then construct an objective function of sparse aperture imaging and parameter estimation using the motion-compensated echo signal represented according to the parameterized characterization dictionary as a constraint condition; An imaging module, used for solving the objective function by using an orthogonal matching pursuit method, and performing Doppler ambiguity number estimation and phase error correction on the moving target to obtain a SAR image of the moving target; Among them, the echo signal obtained by the data acquisition module is: ； The moving direction of the radar is defined as the x-axis, and the direction perpendicular to the radar movement is defined as the y-axis. At speed sports, For radar and moving targets In azimuth time The instantaneous distance is the radar movement speed, ; The clutter suppression module is specifically used to process the echo signal using a shifted phase center antenna to obtain the echo signal after clutter suppression, wherein the echo signal after clutter suppression is obtained through the following formula: ； in, Is a sports goal The retroreflection coefficient, is the distance frequency domain The window function of Indicates the time domain of the direction The window function of Observe moving targets The center time, is the carrier frequency of the transmitted signal, is the propagation speed of electromagnetic waves; The compensation module is specifically used to construct a spectrum analysis reference function according to the following formula: ； The clutter-suppressed echo signal is multiplied by the spectrum analysis reference function to obtain the motion-compensated echo signal obtained by the following formula: ； The post-processing module is specifically used for the first step, using a compressed random sampling method to obtain a compressed sampling matrix of a sparse aperture; The second step is to construct a parameterized characterization dictionary of motion modulation of the moving target based on the motion compensated echo signal; The third step is to divide the parameterized characterization dictionary into two parts, representing linear MTRC and phase modulation respectively; The fourth step is to rewrite the motion-compensated echo signal using the parameterized characterization dictionary, and obtain the motion-compensated echo signal represented by the parameterized characterization dictionary according to the following formula: ； in, , and They are respectively represented as echo signal, Image and system noise, is the compressed sampling matrix of sparse sampling, It is composed of vector and A parameterized dictionary representing the velocity modulation of all moving objects represented by Divided into and Two parts, representing linear MTRC and phase modulation; in, The expression is: In the above formula represents the Fourier transform of the distance dimension, is a scaling factor The scaling transformation of the azimuth dimension, is the unknown Doppler fuzzy number vector of all moving targets, given by Decide; and are discrete numbers in the dimensions of direction and distance respectively; The expression is: in, is the Fourier transform or inverse Fourier transform, It is Adamaj. is a chirped Fourier dictionary, is a constant scaling factor The discrete chirp rate of The objective function of the sparse aperture imaging and parameter estimation is constructed according to the following formula: ， ； in It is a vector -norm; The imaging module is specifically used for the first step, extracting the moving target component by estimating and compensating the moving target, wherein the moving target component is extracted according to the following formula: in, It is The estimated fuzzy number of moving targets, and It is The number of distance and azimuth units of a moving target; The second step is to estimate the phase error of the moving target component, wherein the phase error estimate is obtained according to the following formula: in, For and of The windowing result is It is Estimation of moving objects Signal; and After updating the above formula, the signal component of the moving target can be estimated as: in, It is Estimation of moving targets; Step 3: Calculate the residual component in the following way: Update the echo signal rewritten by the parameterized characterization dictionary in step S4 by subtracting the signal component of the moving target estimated in the first and second steps, and obtain the updated echo signal represented by the following formula: in, It is SAR image components, namely ; Subsequently, the echo signal is updated to , the moving target number is updated to ; Step 4: Iterative solution: Repeat steps 1 to 3 to continuously extract the next moving target by estimating parameters until all moving targets are extracted.

3. An electronic device, characterized in that: It comprises a memory and a processor; the memory stores a computer program, and the processor is used to run the computer program in the memory to execute the steps in the SAR sparse imaging method of a moving target as described in claim 1.

4. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the SAR sparse imaging method for a moving target as claimed in claim 1 are implemented.

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