Method and device for estimating Doppler parameters of moving target of satellite-borne SAR (Synthetic Aperture Radar)

Abstract

The invention discloses a method and a device for estimating Doppler parameters of a satellite-borne SAR (synthetic aperture radar) moving target. The method comprises the following steps: generating a radar echo signal based on a pre-constructed simulation scene of a synthetic aperture radar detection moving target; preprocessing the echo signal to obtain an initial WVD curve of the echo signal; constructing a binary Gaussian matching filtering window based on the coordinate of the maximum amplitude position in the initial WVD curve, and filtering the initial WVD curve by using the filtering window to obtain a filtered WVD curve; calculating points are selected on the filtered WVD curve, a linear equation is fitted based on the selected calculating points, and estimation of the slope and intercept parameters of the linear equation is completed; and inverting the Doppler parameter estimation value of the radar moving target based on the estimated slope and intercept. According to the invention, the Doppler parameter of the moving target can be accurately estimated.

Description

Technical Field

[0001] The present invention relates to the technical field of target detection, and particularly to a method and device for estimating Doppler parameters of spaceborne SAR moving targets. Background Art

[0002] Spaceborne Synthetic Aperture Radar (SAR) has the characteristics of all-weather and all-day operation, being unaffected by cloud cover and other environmental factors, high resolution, and a wide detection range, and has extensive applications in fields such as target recognition and area imaging. With the progress of technology and the requirements of practical applications, synthetic aperture radar technology has developed from traditional stationary target detection and imaging to the detection and imaging of moving targets. However, since target movement introduces additional Doppler center frequencies and Doppler frequency modulation rates, when using the parameters of existing stationary targets for imaging, the imaging results of moving targets will experience defocusing and there will be pixel offsets in the azimuth direction, resulting in low imaging accuracy.

[0003] Therefore, in order to improve the imaging accuracy of moving targets, it is necessary to accurately estimate the Doppler frequency parameters of moving targets to compensate for the imaging results. Summary of the Invention

[0004] The present invention provides a method and device for estimating Doppler parameters of spaceborne SAR moving targets, which can accurately estimate the Doppler parameters of moving targets. The technical solutions are as follows:

[0005] On the one hand, a method for estimating Doppler parameters of spaceborne SAR moving targets is provided, and the method includes:

[0006] Generating radar echo signals based on a pre-constructed simulation scenario of a synthetic aperture radar detecting a moving target;

[0007] Preprocessing the echo signals to obtain an initial WVD curve of the echo signals;

[0008] Constructing a binary Gaussian matching filter window based on the coordinates of the maximum amplitude position in the initial WVD curve, and filtering the initial WVD curve using the filter window to obtain a filtered WVD curve;

[0009] Selecting calculation points on the filtered WVD curve, and fitting a straight-line equation based on the selected calculation points to complete the estimation of the slope and intercept parameters of the straight-line equation;

[0010] Based on the estimated slope and intercept, inversely calculating the estimated value of the Doppler parameters of the radar moving target.

[0011] On the other hand, a device for estimating Doppler parameters of spaceborne SAR moving targets is provided, and the device includes:

[0012] A generating unit, configured to generate a radar echo signal based on a pre-constructed simulation scenario for detecting moving targets by a synthetic aperture radar;

[0013] A preprocessing unit, configured to preprocess the echo signal to obtain an initial WVD curve of the echo signal;

[0014] A filtering unit, configured to construct a binary Gaussian matching filter window based on the coordinates of the maximum amplitude position in the initial WVD curve, and use the filter window to filter the initial WVD curve to obtain a filtered WVD curve;

[0015] A fitting unit, configured to select calculation points on the filtered WVD curve and fit a straight line equation based on the selected calculation points to complete the estimation of the slope and intercept parameters of the straight line equation;

[0016] An inversion unit, configured to invert the estimated Doppler parameter value of the radar moving target based on the estimated slope and intercept.

[0017] On the other hand, a computer device is provided, which includes a memory and a processor. The memory is used to store a computer program, and the processor is used to execute the computer program stored on the memory to implement the steps of the method for estimating the Doppler parameters of spaceborne SAR moving targets described above.

[0018] On the other hand, a computer-readable storage medium is provided. The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for estimating the Doppler parameters of spaceborne SAR moving targets described above are implemented.

[0019] On the other hand, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps of the method for estimating the Doppler parameters of spaceborne SAR moving targets described above are implemented.

[0020] An embodiment of the present invention provides a method for estimating the Doppler parameters of spaceborne SAR moving targets. Since the generated initial WVD curve contains a non-interested area, that is, an interference area, the artifact targets generated by the initial WVD curve will interfere with the estimation accuracy of the Doppler parameters of the moving targets. To eliminate the interference, a binary Gaussian matching filter window is constructed based on the coordinates of the maximum amplitude position in the initial WVD curve, and the initial WVD curve is filtered by using the filter window, so that the interference area can be removed, the artifact targets can be eliminated, and only the interested area is included. On this basis, operations such as point selection and calculation are performed, and the estimated Doppler parameter value of the radar moving target can be accurately inverted. Using the estimated Doppler parameters to compensate the detection results of the moving targets can obtain accurate detection results. Description of the Drawings

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0022] Figure 1 It is a flowchart of a method for estimating Doppler parameters of spaceborne SAR moving targets provided by an embodiment of the present invention;

[0023] Figure 2 It is a structural diagram of a device for estimating Doppler parameters of spaceborne SAR moving targets provided by an embodiment of the present invention;

[0024] Figure 3 It is a hardware architecture diagram of a computer device provided by an embodiment of the present invention;

[0025] Figure 4 It is a schematic diagram of the WVD curve obtained by an existing method provided by an embodiment of the present invention;

[0026] Figure 5 It is a schematic diagram of the WVD curve obtained by the method of this application provided by an embodiment of the present invention. Specific embodiments

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0028] The following describes the specific implementation manners of the above concepts.

[0029] Please refer to Figure 1 , a method for estimating Doppler parameters of spaceborne SAR moving targets provided by an embodiment of the present invention, the method includes:

[0030] Step 100, generating a radar echo signal based on a pre-constructed simulation scenario of a synthetic aperture radar detecting a moving target;

[0031] Step 102, preprocessing the echo signal to obtain an initial WVD curve of the echo signal;

[0032] Step 104: Construct a binary Gaussian matching filter window based on the coordinates of the maximum amplitude position in the initial WVD curve, and use the filter window to filter the initial WVD curve to obtain the filtered WVD curve;

[0033] Step 106: Select calculation points on the filtered WVD curve, and fit a straight-line equation based on the selected calculation points to complete the estimation of the slope and intercept parameters of the straight-line equation;

[0034] Step 108: Based on the estimated slope and intercept, invert the estimated value of the Doppler parameter of the radar moving target.

[0035] In the embodiment of the present invention, since the generated initial WVD curve contains a non-interested area, that is, an interference area, the artifact targets generated by the initial WVD curve will interfere with the estimation accuracy of the Doppler parameter of the moving target. To eliminate the interference, a binary Gaussian matching filter window is constructed based on the coordinates of the maximum amplitude position in the initial WVD curve, and the initial WVD curve is filtered by the filter window, so that the interference area can be removed, the artifact targets can be eliminated, and only the area of interest is obtained. On this basis, operations such as point selection and calculation are performed, and the estimated value of the Doppler parameter of the radar moving target can be accurately inverted. Using the estimated Doppler parameter to compensate the detection result of the moving target, an accurate detection result can be obtained.

[0036] The following describes Figure 1 the execution manner of each step shown.

[0037] First, for step 100:

[0038] The simulation scenario is constructed in the following way:

[0039] Determine the scenario parameters, where the scenario parameters include: radar signal wavelength λ, pulse width tao, bandwidth B w , sampling rate f s , pulse repetition frequency PRF, squint angle number of sampling points N in the azimuth direction a number of sampling points N in the range direction r radar speed v radar radar height h radar downward viewing angle θ, antenna length L a number of layout points Num in the azimuth direction ver number of layout points Num in the range direction hor spacing distance dis between points in the azimuth direction ver spacing distance dis between points in the range direction hor and target range-direction speed V r ;

[0040] Based on the radar height and the downward viewing angle, determine the central coordinates of the simulation scenario;

[0041] Based on the central coordinates, the number of points arranged in the azimuth direction, the number of points arranged in the range direction, the interval distance between points in the azimuth direction, and the interval distance between points in the range direction, determine the size of the arranged dot matrix and the coordinates of each point in the dot matrix to complete the construction of the simulation scenario.

[0042] In this step, the central coordinates of the simulation scenario can be expressed as:

[0043]

[0044] X c ,Y c ,Z c respectively represent the three-dimensional coordinates of the center of the scenario.

[0045] In addition, after the central coordinates are determined, as long as the number of points arranged in the azimuth direction and the number of points arranged in the range direction are known, the size of the dot matrix can be determined, such as 9×10, etc. After the interval distance between points in the azimuth direction and the interval distance between points in the range direction are determined, the coordinates of each point can be known.

[0046] In some embodiments, step 100 includes:

[0047] According to the scenario parameters, calculate other parameters required for the simulation. The other parameters include the reference slant range, the number of effective samples in the range direction, the chirp rate, the synthetic aperture time, and the range gate;

[0048] Based on the scenario parameters, other parameters, and the coordinates of each point in the arranged dot matrix, calculate the slow time axis, the coordinates of the radar in the slow time axis, the coordinates of each point in the arranged dot matrix in the slow time axis, and the fast time axis;

[0049] Based on the calculated slow time axis t a , the coordinates of the radar in the slow time axis (x radar ,y radar ,z radar ), the coordinates of each point in the arranged dot matrix in the slow time axis (x tar ,y tar ,z tar ), and the fast time axis t r , generate the radar echo signal.

[0050] In this embodiment, the reference slant range R ref , the number of effective samples in the range direction Num valid_range , the chirp rate K r , the synthetic aperture time T s , and the range gate dis rangebin are calculated using the following formulas respectively:

[0051]

[0052] For step 102, it includes:

[0053] Step A1: Construct a range compression filter according to the range to the number of sampling points, bandwidth, sampling rate, and chirp rate. For each row of the echo signal, perform the following operations: Transform the current row of the echo signal and the range compression filter into the frequency domain and perform frequency alignment, multiply the aligned echo signal and the range compression filter, and then perform an inverse Fourier transform. Repeat this process for each row until the echo signal after range compression is obtained.

[0054] Step A2: Perform an azimuth Fourier transform on the echo signal after range compression based on the number of azimuth sampling points and the number of range sampling points to obtain the transformed echo signal.

[0055] Step A3: Perform range migration correction on the transformed echo signal to obtain the corrected echo signal.

[0056] Step A4: Calculate the WVD of the corrected echo signal using the interpolation method and plot the initial WVD curve of the echo signal with the azimuth frequency and range frequency as the coordinate axes.

[0057] First, for step A2, the specific process is as follows: Keep the rows of the echo signal after range compression unchanged, traverse each column, perform a Fourier transform on each traversed column and then perform frequency alignment. Repeat this process until each column is traversed to obtain the echo signal after azimuth transformation.

[0058] Second, for step A3, it includes:

[0059] Calculate the azimuth frequency based on the number of azimuth sampling points, the number of range sampling points, and the pulse repetition frequency.

[0060] Calculate the range migration of the moving target based on the azimuth frequency, radar speed, and reference slant range.

[0061] Calculate the phase filter based on the range migration and range frequency.

[0062] Perform a Fourier transform on the echo signal that has completed the azimuth Fourier transform, multiply it by the phase filter, and then perform an inverse Fourier transform on the multiplied echo signal to obtain the echo signal after range migration correction.

[0063] In this step, the calculation formula for the range migration ΔR of the moving target is:

[0064]

[0065] The calculation formula for the phase filter H(f r ) is:

[0066]

[0067] In the formula, j is the imaginary unit, c is the speed of light, and f a is the azimuth frequency, and f is the range frequency r .

[0068] Finally, for step A4, the expression of the initial WVD curve is:

[0069]

[0070] In the formula, W(t, f) represents the WVD of the echo signal x(t); x(t) * is the conjugate of x(t); τ is the integration variable of time; f is the frequency of x(t); t is the time instant.

[0071] For step 104, it includes:

[0072] Determine the row and column where the coordinates of the maximum amplitude position in the initial WVD curve are located;

[0073] Centered on the maximum amplitude position, according to the Gaussian distribution density function, use the following formula to construct the window function of the binary Gaussian matching filter window:

[0074]

[0075] In the formula, g(x, y) is the window function; row and col are respectively the row and column where the coordinates of the maximum amplitude position are located; x and y are respectively the abscissa and ordinate of the WVD curve; and are respectively the attenuation factors of the row and column;

[0076] Filter the initial WVD curve based on the window function to obtain the filtered WVD curve.

[0077] In this step, by constructing the window function and using it to filter the initial WVD curve, the suppression of the non - interesting region in the initial WVD curve can be completed, and the false targets can be eliminated.

[0078] For step 106, it includes:

[0079] Determine the set threshold according to the maximum amplitude of the initial WVD curve;

[0080] For each point on the filtered WVD curve, judge whether its amplitude is not less than the set threshold; if so, take it as a calculation point, if not, do not take it as a calculation point;

[0081] For each selected calculation point, use the least - squares method to fit the straight - line equation and complete the estimation of the slope and intercept parameters of the straight - line equation.

[0082] It should be noted that if too many or too few calculation points are selected, the fitted linear equation will be inaccurate. Therefore, in this application, the threshold is preferably set to 0.3 to 0.4 times the maximum amplitude. In this way, the selected calculation points are closer to the target of interest, and the fitted linear equation is more accurate.

[0083] Finally, for 108, the Doppler parameter estimation value of the radar moving target can be inverted according to the estimated slope and intercept.

[0084] After determining the Doppler parameter estimation value, the detection result of the moving target can be compensated to obtain an accurate detection result.

[0085] To prove the beneficial effects of the method of this application, the inventor compared the estimation effects of the existing method (directly performing Hough transform to select points and fitting a linear equation after calculating the initial WVD curve) and the method of this application using the following embodiments. The simulation parameters used in this embodiment are shown in Table 1:

[0086] Table 1 Simulation Parameters

[0087]

[0088]

[0089] In addition, a single-point target with a range velocity of 30 meters per second is set.

[0090] Based on the above simulation parameters, the existing method and the method of this application are respectively used for calculation and selection of calculation points, and the obtained point selection diagrams are respectively as Figure 4 and Figure 5 shown. It can be seen from the figure that Figure 4 contains two WVD curves, includes non-interest regions, and there are false targets. While Figure 5 due to the addition of a binary Gaussian filter, non-interest regions can be removed, and only real targets are retained.

[0091] It can be seen that the method proposed in this application can effectively suppress the false target generated by WVD, thereby improving the estimation accuracy of the Doppler parameters of the moving target. Using the estimated Doppler parameters to compensate the detection result of the moving target can obtain an accurate detection result.

[0092] As Figure 2 , Figure 3 shown, the embodiment of the present invention provides an estimation device for the Doppler parameters of spaceborne SAR moving targets. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. From the hardware level, as Figure 2 shown, it is a hardware architecture diagram of a computing device where the estimation device for the Doppler parameters of spaceborne SAR moving targets provided by the embodiment of the present invention is located. Except forFigure 2 In addition to the processor, memory, network interface, and non-volatile memory shown, the computing device where the device is located in the embodiments may generally further include other hardware, such as a forwarding chip responsible for processing packets, etc. Taking software implementation as an example, as Figure 3 shown, as a logically meaningful device, it is formed by the CPU of the computing device where it is located reading the corresponding computer program in the non-volatile memory into the memory and running it.

[0093] Please refer to Figure 3 , an embodiment of the present application provides an estimation device for Doppler parameters of spaceborne SAR moving targets, including:

[0094] A generating unit 300, configured to generate a radar echo signal based on a pre-constructed simulation scenario of a synthetic aperture radar detecting a moving target;

[0095] A preprocessing unit 302, configured to preprocess the echo signal to obtain an initial WVD curve of the echo signal;

[0096] A filtering unit 304, configured to construct a binary Gaussian matching filter window based on the coordinates of the maximum amplitude position in the initial WVD curve, and use the filter window to filter the initial WVD curve to obtain a filtered WVD curve;

[0097] A fitting unit 306, configured to select calculation points on the filtered WVD curve and fit a straight line equation based on the selected calculation points to complete the estimation of the slope and intercept parameters of the straight line equation;

[0098] An inversion unit 308, configured to invert the estimated Doppler parameter value of the radar moving target based on the estimated slope and intercept.

[0099] In some embodiments, the simulation scenario is constructed in the following manner:

[0100] Determine the scenario parameters, where the scenario parameters include: radar signal wavelength, pulse width, bandwidth, sampling rate, pulse repetition frequency, squint angle, number of azimuth sampling points, number of range sampling points, radar speed, radar altitude, depression angle, antenna length, number of azimuth arrangement points, number of range arrangement points, azimuth point interval distance, range point interval distance, and target range velocity;

[0101] Based on the radar altitude and depression angle, determine the central coordinates of the simulation scenario;

[0102] Based on the central coordinates, number of azimuth arrangement points, number of range arrangement points, azimuth point interval distance, and range point interval distance, determine the size of the arrangement lattice and the coordinates of each point in the lattice to complete the construction of the simulation scenario.

[0103] In some embodiments, the generating unit 300 is configured to perform the following operations:

[0104] According to the scene parameters, calculate other parameters required for simulation, where the other parameters include the reference slant range, the number of effective sampling points in the range direction, the chirp rate, the synthetic aperture time, and the range gate;

[0105] Based on the scene parameters, other parameters, and the coordinates of each point in the layout lattice, calculate the slow time axis, the coordinates of the radar in the slow time axis, the coordinates of each point in the layout lattice in the slow time axis, and the fast time axis;

[0106] Based on the calculated slow time axis, the coordinates of the radar in the slow time axis, the coordinates of each point in the layout lattice in the slow time axis, and the fast time axis, generate the radar echo signal.

[0107] In some embodiments, the preprocessing unit 302 is configured to perform the following operations:

[0108] According to the number of sampling points in the range direction, the bandwidth, the sampling rate, and the chirp rate, construct a range compression filter; for each row of the echo signal, perform the following operations: transform the current row of the echo signal and the range compression filter into the frequency domain and perform frequency alignment, multiply the aligned echo signal and the range compression filter, and then perform the inverse Fourier transform; until each row is processed, obtain the range-compressed echo signal;

[0109] Based on the number of sampling points in the azimuth direction and the number of sampling points in the range direction, perform an azimuth Fourier transform on the range-compressed echo signal to obtain the transformed echo signal;

[0110] Perform range migration correction on the transformed echo signal to obtain the corrected echo signal;

[0111] Use the interpolation method to calculate the WVD of the corrected echo signal, and plot the initial WVD curve of the echo signal with the azimuth frequency and the range frequency as the coordinate axes.

[0112] In some embodiments, when the preprocessing unit 302 is executing, it performs range migration correction on the transformed echo signal to obtain the corrected echo signal, and is used to perform the following operations:

[0113] Based on the number of sampling points in the azimuth direction, the number of sampling points in the range direction, and the pulse repetition frequency, calculate the azimuth frequency;

[0114] Based on the azimuth frequency, the radar speed, and the reference slant range, calculate the range migration of the moving target;

[0115] Based on the range migration and the range frequency, calculate the phase filter;

[0116] Perform a Fourier transform on the echo signal that has completed the azimuth Fourier transform, multiply it by a phase filter, and then perform an inverse Fourier transform on the multiplied echo signal to obtain the echo signal after range migration correction.

[0117] In some embodiments, the filtering unit 304 is configured to perform the following operations:

[0118] Determine the row and column where the coordinates of the position with the maximum amplitude in the initial WVD curve are located;

[0119] With the position of the maximum amplitude as the center, construct the window function of the binary Gaussian matching filter using the following formula:

[0120]

[0121] In the formula, g(x,y) is the window function; row and col are respectively the row and column where the coordinates of the maximum amplitude position are located; x and y are respectively the abscissa and ordinate of the WVD curve; and are respectively the attenuation factors of the row and column;

[0122] Filter the initial WVD curve based on the window function to obtain the filtered WVD curve.

[0123] In some embodiments, the fitting unit 306 is configured to perform the following operations:

[0124] Determine a set threshold according to the maximum amplitude of the initial WVD curve;

[0125] For each point on the filtered WVD curve, determine whether its amplitude is not less than the set threshold; if so, use it as a calculation point, and if not, do not use it as a calculation point;

[0126] For each selected calculation point, fit a straight line equation using the least squares method and complete the estimation of the slope and intercept parameters of the straight line equation.

[0127] It should be noted that: for the on-board SAR moving target Doppler parameter estimation device provided in the above embodiments, only the above division of each functional module is used for illustration. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the on-board SAR moving target Doppler parameter estimation device provided in the above embodiments and the on-board SAR moving target Doppler parameter estimation method embodiments belong to the same concept, and the specific implementation process can be seen in the method embodiments, which will not be elaborated here.

[0128] The embodiments of the present application also provide a computer device. Please refer to Figure 3, the computer device includes a processor and a memory, and at least one instruction, at least one program, a code set or an instruction set is stored in the memory. The at least one instruction, at least one program, the code set or the instruction set is loaded and executed by the processor to implement the method for estimating the Doppler parameters of spaceborne SAR moving targets provided by the above method embodiments.

[0129] An embodiment of the present application further provides a computer-readable storage medium, on which at least one instruction, at least one program, a code set or an instruction set is stored. The at least one instruction, at least one program, the code set or the instruction set is loaded and executed by the processor to implement the method for estimating the Doppler parameters of spaceborne SAR moving targets provided by the above method embodiments.

[0130] An embodiment of the present application further provides a computer program product, which includes a computer program. The processor of the computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the method for estimating the Doppler parameters of spaceborne SAR moving targets described in any one of the above embodiments.

[0131] For the convenience of description, when describing the above system or device, various modules or units are described separately according to functions. Of course, when implementing the present application, the functions of each unit can be implemented in one or more software and / or hardware.

[0132] From the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments of the present application.

[0133] Finally, it should also be noted that in this text, relational terms such as first, second, third, and fourth are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variation thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising said element.

[0134] The above are only the preferred embodiments of the present application. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present application.

Claims

1. A method for estimating Doppler parameters of a moving target of a spaceborne SAR, characterized in that: The method comprises: Generate radar echo signals based on a pre-built synthetic aperture radar simulation scenario of detecting moving targets; Preprocessing the echo signal to obtain an initial WVD curve of the echo signal; Constructing a binary Gaussian matched filter window based on the coordinates of the maximum amplitude position in the initial WVD curve, and filtering the initial WVD curve using the filter window to obtain a filtered WVD curve; Selecting calculation points on the filtered WVD curve, and fitting a straight line equation based on the selected calculation points to complete the estimation of the slope and intercept parameters of the straight line equation; Based on the estimated slope and intercept, the Doppler parameter estimates of the radar moving target are inverted.

2. The method according to claim 1, characterized in that The simulation scenario is constructed in the following way: Determine scenario parameters, wherein the scenario parameters include: radar signal wavelength, pulse width, bandwidth, sampling rate, pulse repetition frequency, squint angle, number of sampling points in azimuth, number of sampling points in range, radar speed, radar height, downward angle of view, antenna length, number of points arranged in azimuth, number of points arranged in range, distance between points in azimuth, distance between points in range, and target speed in range; Determining the center coordinates of the simulation scene based on the radar height and the downward viewing angle; Based on the center coordinates, the number of points arranged in the azimuth direction, the number of points arranged in the distance direction, the distance between the points in the azimuth direction and the distance between the points in the distance direction, the size of the arranged dot matrix and the coordinates of each point in the dot matrix are determined to complete the construction of the simulation scene.

3. The method according to claim 2, characterized in that The method of generating a radar echo signal based on a pre-built simulation scenario of synthetic aperture radar detecting a moving target includes: Calculate other parameters required for simulation according to the scene parameters, wherein the other parameters include reference slant range, number of effective sampling points in range direction, frequency modulation, synthetic aperture time and range gate; Based on the scene parameters, the other parameters and the coordinates of each point in the arrangement lattice, a slow time axis, the coordinates of the radar in the slow time axis, the coordinates of each point in the arrangement lattice in the slow time axis and a fast time axis are calculated; A radar echo signal is generated based on the calculated slow time axis, the coordinates of the radar in the slow time axis, the coordinates of each point in the arrangement dot matrix in the slow time axis and the fast time axis.

4. The method according to claim 3, characterized in that Preprocessing the echo signal to obtain an initial WVD curve of the echo signal includes: According to the number of sampling points in the distance direction, the bandwidth, the sampling rate and the modulation frequency, a distance compression filter is constructed; for each row of the echo signal, the following steps are performed: converting the echo signal of the current row and the distance compression filter into the frequency domain and performing frequency alignment, multiplying the aligned echo signal and the distance compression filter and performing inverse Fourier transform; until each row is processed to obtain the echo signal after distance compression; Based on the number of sampling points in the azimuth direction and the number of sampling points in the range direction, performing azimuth Fourier transform on the echo signal after range compression to obtain a transformed echo signal; Performing range migration correction on the transformed echo signal to obtain a corrected echo signal; The interpolation method is used to calculate the WVD of the corrected echo signal, and the initial WVD curve of the echo signal is drawn with the azimuth frequency and the range frequency as the coordinate axes.

5. The method according to claim 4, characterized in that The step of performing range migration correction on the transformed echo signal to obtain a corrected echo signal comprises: Calculate the azimuth frequency based on the number of sampling points in the azimuth direction, the number of sampling points in the range direction and the pulse repetition frequency; Calculating the range migration of the moving target based on the azimuth frequency, the radar speed and the reference slant range; Calculating a phase filter based on the range migration and the range frequency; The echo signal that has completed the azimuth Fourier transform is subjected to Fourier transform and multiplied with the phase filter, and the echo signal after the multiplication is subjected to inverse Fourier transform to obtain the echo signal after the range migration correction.

6. The method according to claim 2, characterized in that A binary Gaussian matched filter window is constructed based on the coordinates of the maximum amplitude position in the initial WVD curve, and the initial WVD curve is filtered using the filter window to obtain a filtered WVD curve, including: Determine the row and column where the maximum amplitude position coordinates in the initial WVD curve are located; Taking the maximum amplitude position as the center, the window function of the binary Gaussian matched filter window is constructed using the following formula: Where g(x,y) is the window function; row and col are the row and column where the maximum amplitude position coordinates are located; x and y are the horizontal and vertical coordinates of the WVD curve respectively; and are the attenuation factors for rows and columns respectively; The initial WVD curve is filtered based on the window function to obtain a filtered WVD curve.

7. The method according to claim 1, characterized in that The step of selecting calculation points on the filtered WVD curve and fitting a straight line equation based on the selected calculation points to complete the estimation of the slope and intercept parameters of the straight line equation includes: Determining a set threshold value according to the maximum amplitude of the initial WVD curve; For each point on the filtered WVD curve, determine whether its amplitude is not less than the set threshold; if so, use it as a calculation point, if not, do not use it as a calculation point; For each selected calculation point, the least squares method is used to fit the straight line equation, and the slope and intercept parameters of the straight line equation are estimated.

8. A device for estimating Doppler parameters of a moving target of a spaceborne SAR, characterized in that: The device comprises: A generating unit, for generating a radar echo signal based on a pre-built simulation scenario of synthetic aperture radar detecting a moving target; A preprocessing unit, used for preprocessing the echo signal to obtain an initial WVD curve of the echo signal; A filtering unit, configured to construct a binary Gaussian matched filter window based on the coordinates of the maximum amplitude position in the initial WVD curve, and filter the initial WVD curve using the filter window to obtain a filtered WVD curve; A fitting unit, used for selecting calculation points on the filtered WVD curve, and fitting a straight line equation based on the selected calculation points to complete the estimation of the slope and intercept parameters of the straight line equation; The inversion unit is used to invert the Doppler parameter estimation value of the radar moving target based on the estimated slope and intercept.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the steps of any one of the methods described in claims 1-7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.

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