SAR autofocusing method based on multi-level sub-aperture segmentation

Abstract

The present invention provides a SAR self-focusing method with multi-level sub-aperture segmentation, which relates to the field of radar signal processing technology. In the present invention, the original SAR echo data is preprocessed to obtain a coarsely focused SAR image; then, for the coarsely focused SAR image, the image resolution is reduced by dividing the frequency domain sub-aperture to reduce the image sensitivity to motion errors; then, a model-based or phase gradient-based focusing algorithm is used at each level of sub-aperture to obtain sub-aperture image quality with good focusing effect at each level; and by focusing the sub-apertures step by step, global focusing of the SAR image is finally achieved. Compared with directly dividing multiple sub-apertures, this method not only improves efficiency but also greatly improves the focusing effect of the SAR image, and has been effectively verified in simulations, actual airborne flights, and satellite-borne data.

Description

Technical Field

[0001] The present invention relates to the technical field of radar signal processing, and in particular to a SAR self-focusing method with multi-level sub-aperture segmentation. Background Art

[0002] Synthetic Aperture Radar (SAR), a powerful remote sensing technology, provides high-resolution imaging of the Earth's surface in all weather conditions and is widely used in fields such as geographic surveying and mapping, disaster monitoring, ocean observation, and military reconnaissance. However, due to inherent imperfections in radar systems, unstable aircraft motion, and atmospheric effects, the raw SAR data collected often contains phase errors. These errors can severely affect the focus quality and spatial resolution of the final image, resulting in blurry and distorted images, hindering accurate information extraction and analysis. Therefore, motion compensation is a crucial step in acquiring high-quality SAR images.

[0003] In the related art, common motion compensation methods fall into two categories: sensor-based compensation strategies and echo-based autofocus strategies. In most cases, motion error measurements obtained solely from inertial navigation systems cannot meet the requirements for high-quality SAR imaging. This is particularly serious for light and small platforms that are susceptible to atmospheric disturbances. Furthermore, compared to low-resolution SAR systems, high-resolution SAR systems are more sensitive to motion errors, placing higher demands on error measurement and estimation accuracy. In practical applications, both civilian and military, user requirements for SAR resolution are gradually increasing. Therefore, research on high-precision autofocus algorithms based on echo data is particularly urgent. Echo-based autofocus algorithms are primarily divided into two categories: non-parametric estimation algorithms and model-based parametric estimation algorithms. Non-parametric estimation algorithms offer high accuracy but are highly dependent on the scene, such as requiring strong scattering points. Model-based parametric estimation algorithms have no special scene requirements and offer high estimation efficiency, but the error form and order depend on the model.

[0004] In addition, the above two types of autofocus algorithms are often used in conjunction with sub-apertures, while previous sub-aperture algorithms directly divide the data into multiple sub-apertures for processing. However, since the original data collected by the high-resolution SAR system is seriously contaminated by motion errors, the estimation effect of the first-level sub-aperture is not necessarily good. Summary of the Invention

[0005] (1) Technical problems solved

[0006] In view of the shortcomings of the existing technology, the present invention provides a SAR autofocusing method with multi-level sub-aperture segmentation, which solves the technical problem that the potential of sub-aperture estimation needs to be further explored.

[0007] (2) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] A SAR self-focusing method with multi-level sub-aperture segmentation, comprising:

[0010] Acquire and preprocess raw SAR echo data to obtain coarse-focused SAR images;

[0011] Dividing the coarsely focused SAR image into a plurality of first-order sub-apertures in the azimuth frequency domain;

[0012] moving the Doppler center of each of the first-order sub-apertures to zero frequency;

[0013] Each first-order subaperture adjusted by the Doppler center is evenly divided into a number of second-order subapertures;

[0014] Based on a model or a phase gradient-based focusing algorithm, each of the secondary sub-apertures is subjected to a self-focusing process;

[0015] Resynthesize each secondary sub-aperture after self-focusing into the corresponding primary sub-aperture;

[0016] Based on the model or phase gradient based focusing algorithm, each synthesized first-order sub-aperture is subjected to self-focusing processing;

[0017] Each fully focused first-order sub-aperture is synthesized into a single full-aperture SAR image.

[0018] Preferably, the coarsely focused SAR image is divided into two first-level sub-apertures in the azimuth frequency domain, comprising:

[0019] Multiplying the azimuth frequency domain signal of the coarsely focused SAR image with the initialized matched filter function to obtain a range Doppler signal;

[0020] The range Doppler signal is processed by inverse fast Fourier transform, and its absolute value is taken to obtain left and right sub-aperture images respectively;

[0021] Calculating the relative displacement between the left and right sub-aperture images;

[0022] Calculating an azimuth frequency domain linear modulation rate error based on the relative displacement and the effective Doppler bandwidth;

[0023] Based on the azimuth frequency domain chirp rate error, modifying the matched filter function, and repeating the above operation until the azimuth frequency domain chirp rate error meets a preset accuracy;

[0024] The left and right sub-aperture images finally obtained are output as the two first-level sub-apertures.

[0025] Preferably, the calculation process of the azimuth frequency domain linear modulation rate error includes:

[0026] Assume that the azimuth Doppler spectrum model of the coarse-focused SAR image is as follows:

[0027]

[0028] Where S is the azimuth spectrum after the ideal quadratic phase matching, f a is the azimuth frequency, B d is the Doppler bandwidth, j is the imaginary unit, Δk af is the azimuth frequency modulation error, rect(·) is the rectangular window function, and exp(·) is the exponential function with the natural constant as the base;

[0029] Divide the azimuth into left and right sub-aperture images in the frequency domain:

[0030]

[0031] Among them, S1 and S2 are the azimuth spectra of the left and right sub-aperture images after the azimuth spectrum represents S division;

[0032] The corresponding time domain expression is:

[0033]

[0034] Among them, s1(t a ) and s2(t a ) represent the time domain images corresponding to the left and right sub-aperture images respectively. The first term rect(·) in Equation (4) and Equation (5) is the envelope of the time domain signal. The relative displacement between the left and right sub-aperture images is:

[0035]

[0036] Based on the relationship between the azimuth linear modulation rate, relative displacement, and Doppler bandwidth, the linear modulation rate error in the azimuth frequency domain is obtained as:

[0037]

[0038] Where Δk af is the azimuth frequency domain linear modulation rate error, and Δt is the relative displacement.

[0039] Preferably, the step of evenly dividing each Doppler-center-adjusted primary subaperture into at least two secondary subapertures comprises:

[0040] An azimuth Fourier transform is performed on each first-order subaperture after Doppler center adjustment to evenly divide the effective Doppler bandwidth of the signal into N subbands in the azimuth frequency domain, which serve as N second-order subapertures; where N is a positive integer greater than or equal to 2.

[0041] Preferably, the self-focusing processing of each of the secondary sub-apertures comprises:

[0042] Performing inverse Fourier transform on the N secondary sub-apertures along the azimuth direction to obtain N sub-aperture time domain images;

[0043] Calculate the cross-correlation function between any pair of sub-aperture time domain images and obtain mutual functions;

[0044] Searching for the peak point position corresponding to the cross-correlation function to obtain the offset between the sub-aperture time domain image pair;

[0045] Based on the offset, construct an offset matrix;

[0046] Construct a position offset matrix between any pair of sub-aperture images introduced by 2nd to Nth order phase errors;

[0047] Solving polynomial coefficients of various orders corresponding to N-order phase errors based on the offset matrix and the position offset matrix;

[0048] Based on the polynomial coefficients of each order, a compensation operation is performed to ensure that each of the secondary sub-apertures reaches an optimal focus state.

[0049] Preferably, the calculation process of the polynomial coefficients of each order corresponding to the N-order phase error includes:

[0050] Assume that the error phase contained in the frequency domain of any sub-aperture in the first-level sub-aperture is in the form of an N-order polynomial, excluding linear errors; the phase error model is:

[0051]

[0052] Among them, φ e is the phase error, B sd is the Doppler bandwidth corresponding to the first-order sub-aperture a k is the kth order phase error coefficient in the polynomial phase error model, is the azimuth frequency f a The kth power of , that is, the kth order phase error in the phase error model;

[0053] Divide any sub-aperture in the first-level sub-aperture into N sub-apertures, and the width of the sub-aperture is The phase error within the i-th sub-aperture range is:

[0054]

[0055] Among them, φ i represents the phase error within the i-th sub-aperture, f ai is the center of the i-th sub-aperture, and the expression is:

[0056]

[0057] In the phase error model, through binomial decomposition, it can be seen that the model of the linear phase error component is:

[0058]

[0059] Among them, φ lin,i is the phase error φ within the i-th sub-aperture i The linear error component of is the center of the i-th sub-aperture f ai k-1 power;

[0060] The offset Δ between any two subaperture images i and j i,j for:

[0061]

[0062] The above linear equations are expressed in matrix form, and the position offset matrix Δ is:

[0063] Δ=δa (13)

[0064] in

[0065] Δ=[Δ 1,2 …Δ 1,N Δ 2,3 …Δ 2,N Δ 3,4 …Δ N-1,N ] T (14)

[0066] a=[a2 a3 … a N ] T (15)

[0067]

[0068] Wherein, the superscript T indicates transposition; represents the position offset between the i-th and j-th subaperture images introduced by the k-th order phase error and is defined as follows:

[0069]

[0070] Then the solution of the polynomial error coefficient is approximately:

[0071] a=δ -1 Δ (18)

[0072] Among them, δ -1 is the pseudo-inverse matrix of the position offset matrix δ.

[0073] A multi-level sub-aperture segmentation SAR autofocusing system, comprising:

[0074] An acquisition module is used to acquire and preprocess raw SAR echo data to obtain a coarse-focused SAR image;

[0075] A first-level division module, configured to divide the coarsely focused SAR image into a plurality of first-level sub-apertures in the azimuth frequency domain;

[0076] an adjustment module, configured to move the Doppler center of each of the first-level sub-apertures to zero frequency;

[0077] A secondary division module is used to evenly divide each primary sub-aperture adjusted by the Doppler center into a number of secondary sub-apertures;

[0078] A first autofocusing module is configured to perform autofocusing processing on each of the secondary sub-apertures based on a model or a phase gradient-based focusing algorithm;

[0079] A first synthesis module is used to synthesize each secondary sub-aperture after self-focusing into a corresponding primary sub-aperture;

[0080] A second autofocusing module is used to perform autofocusing on each synthesized first-order sub-aperture based on a model or a phase gradient-based focusing algorithm;

[0081] The second synthesis module is used to synthesize each fully focused first-order sub-aperture into a single full-aperture SAR image.

[0082] A storage medium stores a computer program for SAR autofocusing with multi-level sub-aperture segmentation, wherein the computer program enables a computer to execute the SAR autofocusing method described above.

[0083] An electronic device, comprising:

[0084] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the programs including instructions for executing the SAR autofocusing method as described above.

[0085] (3) Beneficial effects

[0086] The present invention provides a SAR autofocusing method with multi-level sub-aperture segmentation. Compared with the existing technology, it has the following advantages:

[0087] In this method, raw SAR echo data is preprocessed to obtain a coarsely focused SAR image. The coarsely focused SAR image is then divided into frequency-domain subapertures to reduce image resolution and sensitivity to motion errors. A model-based or phase-gradient-based focusing algorithm is then applied to each subaperture level to achieve high-quality images at each subaperture level. By focusing the subapertures step by step, global focusing of the SAR image is ultimately achieved. Compared to directly dividing the image into multiple subapertures, this method significantly improves SAR image focusing while increasing efficiency. This method has been effectively validated in simulations, actual airborne flights, and satellite-borne data. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] 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 use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0089] Figure 1 A block diagram of a SAR autofocusing method with multi-level sub-aperture segmentation provided by an embodiment of the present invention;

[0090] Figure 2 A flowchart of a SAR autofocus algorithm provided by an embodiment of the present invention;

[0091] Figure 3 A diagram illustrating the concept of an autofocusing algorithm based on multi-level aperture segmentation provided by an embodiment of the present invention (taking two-level sub-aperture as an example);

[0092] Figures 4(a) to 4(b) They are respectively the imaging results of the uncompensated simulation scene and the azimuth imaging results of a single target provided by the embodiments of the present invention;

[0093] Figures 5(a) to 5(b) They are respectively the imaging result after the multi-stage sub-aperture compensation and the azimuth imaging result of a single target provided by the embodiments of the present invention;

[0094] Figures 6(a) to 6(b) They are respectively the imaging result after the traditional single-stage sub-aperture compensation and the azimuth imaging result of a single target provided by the embodiments of the present invention;

[0095] Figure 7 、 Figure 8 Schematic diagrams of front and back azimuthal slices of the first-level sub-aperture 1 and the first-level sub-aperture 2 provided in embodiments of the present invention;

[0096] Figure 9 A schematic diagram of an azimuthal slice after synthesis of an original image and a sub-aperture according to an embodiment of the present invention;

[0097] Figure 10 A schematic diagram of an azimuthal slice after refocusing after subaperture synthesis provided by an embodiment of the present invention;

[0098] Figure 11 A SAR original image provided by an embodiment of the present invention;

[0099] Figure 12 A SAR image focused using the proposed algorithm provided in an embodiment of the present invention;

[0100] Figure 13 、 Figure 14 Schematic diagrams of front and back azimuthal slices of the first-level sub-aperture 1 and the first-level sub-aperture 2 provided in embodiments of the present invention;

[0101] Figure 15 A schematic diagram of an azimuthal slice after synthesis of an original image and a sub-aperture according to an embodiment of the present invention;

[0102] Figure 16 A schematic diagram of direct multi-aperture and multi-level sub-aperture azimuthal slicing provided by an embodiment of the present invention;

[0103] Figure 17 A "Sentinel-1" SAR original image provided by an embodiment of the present invention;

[0104] Figure 18 A SAR image obtained through direct multi-subaperture focusing provided by an embodiment of the present invention;

[0105] Figure 19 A SAR image focused using the proposed algorithm provided in an embodiment of the present invention;

[0106] Figures 20(a) to 20(b) These are point target performance diagrams of subaperture 1 before secondary subaperture focusing and after multi-stage subaperture focusing provided by the embodiments of the present invention;

[0107] Figure 21 A schematic diagram of the front and rear azimuthal slices of the first-level sub-aperture 1 focusing according to an embodiment of the present invention;

[0108] Figures 22(a) to 22(b) These are point target performance diagrams of sub-aperture 3 before and after focusing of the secondary sub-aperture provided by an embodiment of the present invention;

[0109] Figure 23 A schematic diagram of the front and rear azimuthal slices of the first-level sub-aperture 2 focusing according to an embodiment of the present invention;

[0110] Figures 24(a) to 24(b) The target masses before and after the multi-stage sub-aperture processing provided by the embodiment of the present invention are respectively before and after the multi-stage sub-aperture focusing;

[0111] Figure 25 A schematic diagram of an azimuthal slice after synthesis of an original image and a sub-aperture according to an embodiment of the present invention;

[0112] Figures 26(a) to 26(b) Schematic diagrams of point targets of direct multi-subaperture and multi-level subaperture provided in embodiments of the present invention respectively;

[0113] Figure 27 Schematic diagram of direct multi-aperture and multi-level sub-aperture azimuthal slicing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0114] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0115] The embodiments of the present application provide a SAR autofocusing method with multi-level sub-aperture segmentation, thereby solving the technical problem that the potential of sub-aperture estimation needs to be further explored.

[0116] The technical solution in the embodiments of the present application is to solve the above technical problems, and the overall idea is as follows:

[0117] Considering that existing sub-aperture algorithms directly divide data into multiple sub-apertures for processing, and do not further perform secondary sub-aperture division on the obtained sub-apertures, and the original data collected by high-resolution SAR systems are seriously contaminated by motion errors, it is necessary to further explore the potential of sub-aperture estimation. The embodiment of the present invention proposes a SAR self-focusing algorithm based on frequency domain multi-level sub-aperture segmentation for high-resolution SAR imaging systems. The basic idea is to reduce the image resolution and reduce the image sensitivity to motion errors by dividing the frequency domain sub-aperture, and then use a model-based or phase gradient-based focusing algorithm at each level of sub-aperture to obtain sub-aperture image quality with good focusing effect at each level. By focusing the sub-aperture step by step, the global focusing of the SAR image is finally achieved.

[0118] It should be noted that this application pioneered the concept of "multi-level sub-aperture", which refers to the result obtained by dividing the SAR image into sub-apertures layer by layer.

[0119] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0120] Example 1:

[0121] like Figure 1 As shown, an embodiment of the present invention provides a SAR autofocusing method with multi-level sub-aperture segmentation, including:

[0122] S1. Acquire and preprocess raw SAR echo data to obtain a coarse-focused SAR image;

[0123] S2. Dividing the coarsely focused SAR image into a plurality of first-order sub-apertures in the azimuth frequency domain;

[0124] S3, moving the Doppler center of each of the first-level sub-apertures to zero frequency;

[0125] S4, evenly dividing each first-level sub-aperture adjusted by the Doppler center into a number of second-level sub-apertures;

[0126] S5, performing self-focusing processing on each of the secondary sub-apertures based on a model or a phase gradient-based focusing algorithm;

[0127] S6, resynthesizing each secondary sub-aperture after self-focusing into a corresponding primary sub-aperture;

[0128] S7, performing self-focusing processing on each synthesized first-order sub-aperture based on a model or phase gradient-based focusing algorithm;

[0129] S8. Combining each fully focused first-order sub-aperture into a single full-aperture SAR image.

[0130] Compared with directly dividing multiple sub-apertures, the example of the present invention improves efficiency and greatly improves the focusing effect of SAR images, and has been effectively verified in simulation, actual airborne flight and satellite-borne data.

[0131] like Figure 2 As shown, Figure 2 A flowchart for a SAR autofocusing algorithm is disclosed. First, the raw data is divided into multiple time-domain subapertures, and the echoes corresponding to each time-domain aperture are imaged separately. Each subimage is then divided into multiple subaperture levels, and focusing is performed on each subaperture level, ultimately estimating high-order motion errors and focusing the image. The focusing sequence begins with the deeper subapertures, and after completing the secondary focusing, the subapertures are synthesized to the next higher level, and then processed upwards, level by level, ultimately returning to the original image domain.

[0132] The principle of the algorithm is explained using two-level sub-aperture as an example. Figure 3As shown. First, the frequency domain is divided into two sub-apertures, and then multi-aperture processing is performed on each of the two sub-apertures. The two sub-aperture images obtained by processing are combined into one image, and then autofocusing is performed to obtain a focused SAR image. Taking the second-level sub-aperture division as an example, the effectiveness of the idea is explained by combining the MD (Map Drift) algorithm and the MAM (Multiple Aperture Map Drift) algorithm:

[0133] In step S1, raw SAR echo data is acquired and preprocessed to obtain a coarsely focused SAR image.

[0134] In this step, the original SAR echo data is preliminarily processed by motion compensation, two-dimensional focusing, etc. to obtain a coarsely focused SAR image.

[0135] It is understandable that although the resolution of coarse-focused SAR images in range and azimuth is relatively low and cannot clearly distinguish the detailed features of the target, compared with the original SAR data, they can still show the basic outline and general structure of the target scene.

[0136] In addition, the embodiment of the present invention does not limit the source of the original SAR echo data. Whether it is from actual airborne flight data, spaceborne SAR satellite data, or data collected by other equipment equipped with high-resolution SAR, it can be used as the processing object of this step.

[0137] In step S2, the coarsely focused SAR image is divided into a number of first-order sub-apertures in the azimuth frequency domain.

[0138] This step divides the acquired coarsely focused SAR image into multiple first-order sub-apertures in the azimuth frequency domain. This process, fundamental to the entire algorithm, segments the original SAR image into multiple sub-aperture images with lower azimuth resolution by segmenting the Doppler spectrum. This approach makes the acquired sub-images less sensitive to errors, easier to focus, and allows for increased processing efficiency through parallel computing. This division also lays the foundation for subsequent focusing and synthesis operations, enabling the algorithm to gradually refine image details and ultimately achieve high-resolution imaging.

[0139] Specifically, this step includes:

[0140] S21 : multiplying the azimuth frequency domain signal of the coarsely focused SAR image by an initialized matched filter function to obtain a range Doppler signal.

[0141] S22 . Process the range Doppler signal using inverse fast Fourier transform, and take its absolute value to obtain left and right sub-aperture images respectively.

[0142] S23: Calculate the relative displacement between the left and right sub-aperture images.

[0143] S24. Calculate an azimuth frequency-domain linear modulation rate error based on the relative displacement and the effective Doppler bandwidth.

[0144] S25 , based on the azimuth frequency domain chirp rate error, correct the matched filter function, and repeat the above operations of S21 to S24 until the azimuth frequency domain chirp rate error meets the preset accuracy.

[0145] S26 , outputting the left and right sub-aperture images finally obtained as the two first-level sub-apertures.

[0146] In an optional implementation, the calculation process of the azimuth frequency domain chirp rate error includes:

[0147] Assume that the azimuth Doppler spectrum model of the coarse-focused SAR image is as follows:

[0148]

[0149] Where S is the azimuth spectrum after the ideal quadratic phase matching, f a is the azimuth frequency, B d is the Doppler bandwidth, j is the imaginary unit, Δk af is the azimuth frequency modulation error, rect(·) is the rectangular window function, and exp(·) is the exponential function with a natural constant as the base.

[0150] In the frequency domain, the azimuth direction is divided into left and right sub-aperture images:

[0151]

[0152] Among them, S1 and S2 are the azimuth spectra of the left and right sub-aperture images after the azimuth spectrum is divided by S.

[0153] The corresponding time domain expression is:

[0154]

[0155] Among them, s1(t a ) and s2(t a ) represent the time domain images corresponding to the left and right sub-aperture images respectively. The first term rect(·) in Equation (4) and Equation (5) is the envelope of the time domain signal. The relative displacement between the left and right sub-aperture images is:

[0156]

[0157] Based on the relationship between the azimuth linear modulation rate, relative displacement, and Doppler bandwidth, the linear modulation rate error in the azimuth frequency domain is obtained as:

[0158]

[0159] Where Δk af is the azimuth frequency domain linear modulation rate error, and Δt is the relative displacement.

[0160] In particular, when performing the above operation to obtain the azimuth frequency domain linear modulation rate error, it is necessary to pay attention to the following points:

[0161] 1) Block Calculation: To reduce the impact of noise and improve parameter estimation accuracy, it is usually necessary to perform block calculations along the distance term. For example, a parameter is calculated every 50 distance units. This block calculation method can effectively reduce the impact of noise on signal processing and improve the accuracy of parameter estimation.

[0162] 2) Selecting the number of range bins: The number of range bins should not be too large. Within the selected range, the Doppler frequency variation should be negligible. This is because an excessively large number of range bins may cause the Doppler frequency variation to be too significant, thus affecting signal processing accuracy. Generally speaking, the appropriate number of range bins should be selected based on the specific application scenario and signal characteristics.

[0163] 3) Polynomial Fitting: Finally, a second-order polynomial fit is performed on the multiple estimation results obtained along the range direction. This step further eliminates the effects of noise and improves the stability and reliability of signal processing. Polynomial fitting is a common mathematical method that smoothes data by fitting a curve, thereby removing interference caused by noise.

[0164] In step S3, the Doppler center of each of the first-order sub-apertures is moved to zero frequency.

[0165] After obtaining the first-level sub-aperture, this step requires moving the Doppler center of each sub-aperture to zero frequency. This adjustment step is crucial, as it allows standardization within each sub-aperture when performing the second-level sub-aperture division. The division of the first-level sub-aperture causes the equivalent Doppler center of each sub-aperture SAR image to shift. By moving the Doppler center frequency to zero, the Doppler center of the first-level sub-aperture is consistent with the Doppler center of the original SAR image, thereby providing a more accurate signal basis for the subsequent sub-aperture division and focusing process. In addition, zero Doppler alignment also ensures the alignment of the sub-apertures in the frequency domain, which paves the way for effective synthesis of subsequent levels, enabling the algorithm to smoothly transmit and process signals between different levels.

[0166] In step S4, each Doppler-center-adjusted primary sub-aperture is evenly divided into a number of secondary sub-apertures.

[0167] After Doppler center adjustment, each primary sub-aperture has similar properties to the original SAR image. Therefore, this step uses a similar method to the primary sub-aperture division, evenly dividing each primary sub-aperture into multiple smaller secondary sub-apertures. This secondary division allows the algorithm to perform more detailed and localized processing.

[0168] Specifically, this step includes:

[0169] An azimuth Fourier transform is performed on each first-order subaperture after Doppler center adjustment to evenly divide the effective Doppler bandwidth of the signal into N subbands in the azimuth frequency domain, which serve as N second-order subapertures; where N is a positive integer greater than or equal to 2.

[0170] In step S5, each of the secondary sub-apertures is subjected to a self-focusing process based on a model or a phase gradient-based focusing algorithm.

[0171] At this level, this step applies autofocusing techniques to each secondary sub-aperture to correct phase errors and enhance image clarity. Autofocusing, a key technology for improving SAR imaging quality, involves algorithms such as PGA and MAM. These algorithms estimate and compensate for phase errors caused by motion, ensuring optimal focus for each sub-aperture. Operating at this finer level, the algorithm can address local distortions that might be overlooked in coarser decomposition. In some complex terrain or target scenes, localized motion errors or signal distortions may be difficult to detect with coarse decomposition, but can be effectively detected and corrected in the secondary sub-aperture processing. Through this layered and refined focusing approach, the algorithm can gradually optimize image details and improve image quality. The MAM algorithm can be used for focusing the secondary sub-apertures because it exhibits good performance and robustness when processing certain types of SAR data.

[0172] Specifically, this step includes:

[0173] S51, performing inverse Fourier transform on the N secondary sub-apertures along the azimuth direction to obtain N sub-aperture time domain images;

[0174] S52, calculate the cross-correlation function between any pair of sub-aperture time domain images, and obtain mutual functions;

[0175] S53, searching for the peak point position corresponding to the cross-correlation function to obtain the offset between the sub-aperture time domain image pairs;

[0176] S54, constructing an offset matrix based on the offset;

[0177] S55, constructing a position offset matrix between any sub-aperture image pairs introduced by 2nd to Nth order phase errors;

[0178] S56. Solving polynomial coefficients of various orders corresponding to the N-order phase error based on the offset matrix and the position offset matrix;

[0179] S57. Based on the coefficients of the polynomials of various orders, a compensation operation is performed to ensure that each of the secondary sub-apertures reaches an optimal focusing state.

[0180] In an optional implementation, the calculation process of the polynomial coefficients of each order corresponding to the N-order phase error includes:

[0181] Assume that the error phase contained in the frequency domain of any sub-aperture in the first-level sub-aperture is in the form of an N-order polynomial, excluding linear errors; the phase error model is:

[0182]

[0183] Among them, φ e is the phase error, B sd is the Doppler bandwidth corresponding to the first-order sub-aperture a k is the kth order phase error coefficient in the polynomial phase error model, is the azimuth frequency f a The kth power of , that is, the kth order phase error in the phase error model.

[0184] Divide any sub-aperture in the first-level sub-aperture into N sub-apertures, and the width of the sub-aperture is The phase error within the i-th sub-aperture range is:

[0185]

[0186] Among them, φ i represents the phase error within the i-th sub-aperture, f ai is the center of the i-th sub-aperture, and the expression is:

[0187]

[0188] In the phase error model, through binomial decomposition, we can know that the model of the linear phase error component is:

[0189]

[0190] Among them, φ lin,i is the phase error φ within the i-th sub-aperture i The linear error component of is the center of the i-th sub-aperture f aito the k-1 power.

[0191] The offset Δ between any two subaperture images i and j i,j for:

[0192]

[0193] The above linear equations are expressed in matrix form, and the position offset matrix Δ is:

[0194] Δ=δa (13)

[0195] in

[0196] Δ=[Δ 1,2 …Δ 1,N Δ 2,3 …Δ 2,N Δ 3,4 ]Δ N-1,N ] T (14)

[0197] a=[a2 a3 … a N ] T (15)

[0198]

[0199] Wherein, the superscript T indicates transposition; represents the position offset between the i-th and j-th subaperture images introduced by the k-th order phase error and is defined as follows:

[0200]

[0201] Then the solution of the polynomial error coefficient is approximately:

[0202] a=δ -1 Δ (18)

[0203] Among them, δ -1 is the pseudo-inverse matrix of the position offset matrix δ.

[0204] In step S6, each secondary sub-aperture after self-focusing is resynthesized into a corresponding primary sub-aperture.

[0205] After individually focusing the secondary sub-apertures, this step recombines these focused secondary sub-apertures into their respective primary sub-apertures. This synthesis step is a crucial component of the algorithm, combining the locally optimized sub-apertures into a larger, more coherent unit. During the synthesis process, the algorithm must ensure phase continuity and amplitude consistency between the synthesized sub-apertures. This is because phase discontinuities or amplitude inconsistencies during the synthesis process can cause artifacts or distortion in the image, affecting the final imaging result.

[0206] Through a carefully designed synthesis algorithm, the focused segments can be seamlessly combined to form a first-order sub-aperture with a larger effective Doppler bandwidth while preserving the improvements made by autofocusing. This step is crucial to maintaining the integrity of the SAR image when it is returned to a coarser level, providing high-quality intermediate results for subsequent further processing.

[0207] In step S7, each synthesized primary sub-aperture is subjected to a self-focusing process based on a model or a phase gradient-based focusing algorithm.

[0208] With the synthesized first-order sub-aperture, this step applies a focusing process to it to further improve its quality. This step utilizes the corrections made in the previous stages to ensure that the first-order sub-aperture is accurately focused. At this stage, various self-focusing techniques can also be used for processing, such as phase gradient autofocusing (PGA), MD, or MAM. These technologies can automatically adjust the focusing parameters based on the characteristics and errors of the image, thereby enhancing the sharpness and resolution of the sub-aperture. The focusing of the first-order sub-aperture can be processed using the MD algorithm. This step is the final preparation before reconstructing the full-aperture SAR image. Through the focusing process at this stage, it can be ensured that the first-order sub-aperture reaches the optimal imaging state before entering the final synthesis stage.

[0209] It should be noted that the focusing algorithm used here can be the same as or different from step S5. Of course, in an optional embodiment, the calculation process of the two focusing points before and after can be limited to be consistent. Correspondingly, you can refer to the self-focusing processing process in step S5, which will not be repeated here.

[0210] In step S8, each fully focused primary sub-aperture is synthesized into a single full-aperture SAR image.

[0211] In this step, the fully focused first-order sub-apertures are synthesized into a single full-aperture SAR image. This synthesis step combines all the corrected and focused sub-apertures into a coherent high-resolution image.

[0212] Specifically, this step involves first restoring the Doppler center of each first-order sub-aperture to its original true Doppler center. Then, the focused full-aperture Doppler spectrum is reconstructed in the Doppler domain. Finally, the full-aperture Doppler spectrum is inverse Fourier transformed to obtain a reconstructed, focused full-aperture SAR image.

[0213] So far, the embodiment of the present invention has completed the entire process of the SAR autofocusing method with multi-level sub-aperture segmentation.

[0214] By dividing the aperture into multiple sub-apertures, high-order motion errors can be effectively estimated while also reducing the computational complexity compared to directly dividing the aperture into multiple sub-apertures. Whether directly dividing the aperture into multiple sub-apertures or dividing the aperture into multiple sub-apertures for polynomial error estimation, the core operation that consumes the most computational time is the cross-correlation operation.

[0215] Therefore, in order to illustrate that the multi-level sub-aperture self-focusing method can reduce the amount of calculation, the number of cross-correlation operations of the two sub-aperture division methods is statistically analyzed:

[0216] Directly dividing the aperture into 2N sub-apertures requires L1 cross-correlation operations to solve the polynomial coefficients. The expression of L1 is:

[0217]

[0218] First, the first-level sub-aperture is divided into two sub-apertures, and then the second-level sub-aperture is divided into N sub-apertures. L2 cross-correlation operations are required to solve the polynomial coefficients at each level. The expression is:

[0219]

[0220] L1-L2=N-1 (21)

[0221] In general, the number of secondary sub-apertures satisfies N≥2, and the number of cross-correlation operations required for multi-level sub-apertures is less than that for direct sub-aperture division.

[0222] In addition, to verify the effectiveness of the proposed algorithm, a simulation experiment analysis was carried out. The simulation system parameters are shown in Table 1.

[0223] Table 1 Simulation system parameters

[0224] parameter Numerical Center frequency 14.25GHz bandwidth 500MHz Platform speed 100m / s Pulse repetition frequency 2000Hz Pulse width 500us

[0225] The imaging results without compensation are as follows Figures 4(a) to 4(b) As shown in Figure 4(b), the azimuth slice of a single target has an azimuth resolution of 0.4219m and a peak-to-sidelobe ratio of -3.2dB. Figures 5(a) to 5(b) As shown in the figure, after multi-level sub-aperture error estimation and compensation, the azimuth resolution is 0.1422m, the peak sidelobe ratio is -12.56dB, and the integrated sidelobe ratio is -11.05dB. Figures 6(a) to 6(b) As shown, the azimuth resolution of the traditional single-stage subaperture is 0.1452, the peak sidelobe ratio is -11.18dB, and the integrated sidelobe ratio is -9.93dB.

[0226] like Figure 7As shown in the figure, the MAM processing results of sub-aperture 1 are analyzed using the secondary sub-aperture image. Before focusing, the azimuth resolution is 0.9375m, and the peak sidelobe ratio is -5.37dB; after MAM: the azimuth resolution is 0.2672m, the peak sidelobe ratio is -12.69dB, and the integrated sidelobe ratio is -11.63dB.

[0227] like Figure 8 As shown in the figure, the results of MAM processing of sub-aperture 2 are analyzed: without MAM, the azimuth resolution is 0.7469m, and the peak-to-sidelobe ratio is -2.46dB; with MAM, the azimuth resolution is 0.2781m, the peak-to-sidelobe ratio is -11.00dB, and the integrated sidelobe ratio is -7.66dB.

[0228] like Figure 9 As shown, the full aperture after the two sub-apertures are synthesized, before synthesis: the azimuth resolution is 1.98m; after synthesis: the azimuth resolution is 0.1359m, the peak sidelobe ratio is -7.15dB, and the integrated sidelobe ratio is -6.16dB.

[0229] like Figure 10 As shown, the synthesised image is focused, and the polynomial coefficients are solved using the relative relationship between the already focused first-order sub-apertures. The processing effect is as follows. The green line is the image slice after refocusing, and the resolution, integrated sidelobe ratio, and peak sidelobe ratio are optimized.

[0230] Furthermore, in order to verify the effectiveness of the proposed algorithm, focusing processing was performed on the actual airborne flight L-band data and the Sentinel-1 spaceborne SAR satellite data:

[0231] First, the proposed algorithm is used to focus the actual flight L-band SAR data. The system parameters are shown in Table 2.

[0232] Table 2 Simulation system parameters

[0233] parameter Numerical Center frequency 1.3GHz bandwidth 200MHz Platform speed 70m / s Pulse repetition frequency 1000Hz Pulse width 10us Flight altitude 5.1km

[0234] After the original data is motion compensated by the inertial navigation data, the imaging result is as follows Figure 11 As shown in the figure, it can be seen that although compensation has been made using inertial navigation data, residual errors still exist and affect the focus of the image.

[0235] The SAR original image processed as above is processed by the proposed frequency domain multi-level sub-aperture autofocusing algorithm. The processing results are as follows: Figure 12 As shown. Figure 11 Compared with the image focusing effect, the focusing effect has been greatly improved. In order to evaluate the performance of the algorithm, point targets in the scene were selected and their focusing effects at various sub-apertures were quantitatively analyzed.

[0236] Subaperture 1 is divided into three subapertures in the secondary subaperture. After MAM focusing processing, the improved SAR image corresponding to subaperture 1 is obtained. For the front film of the point target before and after processing, Figure 13 As shown in the figure, the red and green curves are before and after focusing, respectively. Before focusing, the azimuth slice has an azimuth resolution of 2.707m, a peak sidelobe ratio of -5dB, and an integrated sidelobe ratio of -4.68dB. After focusing, the azimuth slice has an azimuth resolution of 1.8165m, a peak sidelobe ratio of -10.19dB, and an integrated sidelobe ratio of -6.2918dB. From an intuitive and specific perspective, the focusing effect of the first-order subaperture 1 has been greatly improved.

[0237] The same operation is performed on sub-aperture 2 as on sub-aperture 1, and the point target slices before and after processing are obtained, as shown in the following example: Figure 14 As shown in the figure, the red and green curves are before and after focusing, respectively. Before focusing, the azimuth slice has an azimuth resolution of 2.903m, a peak sidelobe ratio of -6.27dB, and an integrated sidelobe ratio of -8.298dB. After focusing, the azimuth slice has an azimuth resolution of 1.6384m, a peak sidelobe ratio of -12.65dB, and an integrated sidelobe ratio of -9.44dB. From an intuitive and specific perspective, the focusing effect of the first-order subaperture 2 has been greatly improved.

[0238] The first-order sub-aperture after focusing is directly synthesized, and the original SAR image and the image azimuth slice after synthesis are compared. Figure 15 As shown in the figure, the red and green curves are before and after focusing, respectively. Before focusing, the azimuth slice has an azimuth resolution of 3.2412m, a peak sidelobe ratio of -4.25dB, and an integrated sidelobe ratio of -4.69dB. After focusing, the azimuth slice has an azimuth resolution of 1.2644m, a peak sidelobe ratio of -7.5152dB, and an integrated sidelobe ratio of -9.49dB. From an intuitive and specific perspective, the focusing of the first-order sub-aperture greatly improves the quality of the original SAR image.

[0239] Since there is still an offset and error between the two sub-apertures, the focusing parameters are extracted based on the relationship between the two amplitudes. The target azimuth slice is as follows: Figure 16 As shown in the figure, the red and green curves represent the cases of direct and multi-level subaperture division, respectively. Before focusing, the azimuth slice has an azimuth resolution of 0.9973m, a peak sidelobe ratio of -16.42dB, and an integrated sidelobe ratio of -13.57dB. After focusing, the azimuth slice has an azimuth resolution of 0.9261m, a peak sidelobe ratio of -17.74dB, and an integrated sidelobe ratio of -17.88dB. From an intuitive and specific perspective, the multi-level subaperture method significantly improves the quality of the original SAR image.

[0240] Then, the proposed algorithm is used to focus the Sentinel-1 spaceborne SAR data. The system parameters are shown in Table 3.

[0241] Table 3 SAR system parameters

[0242] parameter Numerical Center frequency 5.4GHz bandwidth 42.2MHz Sampling rate 46.9MHz Platform speed 7000m / s Pulse repetition frequency 1663.5Hz Pulse width 51.1us

[0243] After the original data is motion compensated by the inertial navigation data, the imaging result is as follows Figure 17 As shown in the figure, it can be seen that although compensation has been made using inertial navigation data, residual errors still exist and affect the focus of the image.

[0244] The SAR original image after the above processing is directly divided into 5 sub-apertures for focusing processing, and the polynomial coefficients of the error are estimated in the frequency domain. The processing results are as follows: Figure 18 As shown, Figure 17 Compared with the image focusing effect has been greatly improved.

[0245] The SAR original image processed as above is processed by the proposed frequency domain multi-level sub-aperture autofocusing algorithm. The processing results are as follows: Figure 19 As shown. Figure 17 and Figure 18 Compared with the image focusing effect, the focusing effect has been greatly improved. In order to evaluate the performance of the algorithm, point targets in the scene were selected and their focusing effects at various sub-apertures were quantitatively analyzed.

[0246] Sub-aperture 1 is divided into three sub-apertures in the secondary sub-aperture. After MAM focusing, the improved SAR image corresponding to sub-aperture 1 is obtained, and the point targets in the scene are extracted. As shown in Figure 20, after secondary sub-aperture focusing, the imaging effect of point targets in the scene is greatly improved. Slice analysis of point targets before and after processing is performed, as shown in Figure 20. Figure 21 As shown in the figure, the red and green curves are before and after focusing, respectively. Before focusing, the azimuth slice has an azimuth resolution of 34.9794m, a peak sidelobe ratio of -5.2301dB, and an integrated sidelobe ratio of -6.3191dB. After focusing, the azimuth slice has an azimuth resolution of 15.1227m, a peak sidelobe ratio of -14.0826dB, and an integrated sidelobe ratio of -8.8524dB. From an intuitive and specific perspective, the focusing effect of the first-order subaperture 1 has been greatly improved.

[0247] The same operation is performed on sub-aperture 2 as on sub-aperture 1, and the point target in the scene is extracted. As shown in Figure 22, after the secondary sub-aperture focusing, the imaging effect of the point target in the scene is greatly improved. Figure 23As shown in the figure, the red and green curves are before and after focusing, respectively. Before focusing, the azimuth slice resolution is 33.1384m, the peak sidelobe ratio is -2.7446dB, and the integrated sidelobe ratio is -2.9529dB. After focusing, the azimuth slice resolution is 11.1776m, the peak sidelobe ratio is -14.7018dB, and the integrated sidelobe ratio is -9.6112dB. From the intuitive and specific indicators, the focusing effect of the first-order sub-aperture 2 has been greatly improved.

[0248] The first-order sub-aperture after focusing is directly synthesized. The comparison of the point target graphics and azimuth slices in the original SAR image and the synthesized image is shown in Figures 24 and 25, respectively. Figure 25 In Figure 24, (a) and (b) are the imaging results of the point target before and after using multi-level sub-aperture focusing. It can be clearly seen that the point target focusing effect is greatly improved after the proposed algorithm is processed. The point target in Figure 24 is analyzed in azimuth direction, and the obtained Figure 25 The red and green curves are before and after focusing, respectively. Before focusing, the azimuth slice has an azimuth resolution of 110.9873m. The target is severely defocused and fragmented, making the calculation of the peak sidelobe ratio and the integrated sidelobe ratio meaningless. After focusing, the azimuth slice has an azimuth resolution of 8.4161m, a peak sidelobe ratio of -17.3265dB, and an integrated sidelobe ratio of -14.4211dB. From an intuitive and concrete perspective, focusing the first-order subaperture significantly improves the quality of the original SAR image. (Imaging azimuth weighting - Taylor window).

[0249] Since there is still an offset and error between the two sub-apertures, the focusing parameters are extracted based on the relationship between the two amplitudes. The final multi-level sub-aperture focusing SAR image is compared with the direct division of multiple sub-aperture focusing method, as shown in Figures 26 and Figure 27 In Figure 26, (a) and (b) are the imaging results of point targets before and after using multiple sub-apertures and multi-level sub-aperture focusing, respectively. It can be clearly seen that the focusing effect of point targets is greatly improved after the proposed algorithm is processed. The point target in Figure 26 is analyzed in azimuth direction, and the obtained Figure 27 The red and green curves represent the cases of direct multiple subaperture division and multi-level subaperture division, respectively. Direct multiple subaperture slicing achieves an azimuth resolution of 8.0216m, a peak sidelobe ratio of -17.439dB, and an integrated sidelobe ratio of -15.05391dB. After focusing, azimuth slicing achieves an azimuth resolution of 7.1011m, a peak sidelobe ratio of -21.0164dB, and an integrated sidelobe ratio of -17.8426dB. The multi-level subaperture approach significantly improves the quality of raw SAR images, both intuitively and in concrete terms.

[0250] Example 2:

[0251] An embodiment of the present invention provides a SAR autofocusing system with multi-level sub-aperture segmentation, comprising:

[0252] An acquisition module is used to acquire and preprocess raw SAR echo data to obtain a coarse-focused SAR image;

[0253] A first-level division module, configured to divide the coarsely focused SAR image into a plurality of first-level sub-apertures in the azimuth frequency domain;

[0254] an adjustment module, configured to move the Doppler center of each of the first-level sub-apertures to zero frequency;

[0255] A secondary division module is used to evenly divide each primary sub-aperture adjusted by the Doppler center into a number of secondary sub-apertures;

[0256] A first autofocusing module is configured to perform autofocusing processing on each of the secondary sub-apertures based on a model or a phase gradient-based focusing algorithm;

[0257] A first synthesis module is used to synthesize each secondary sub-aperture after self-focusing into a corresponding primary sub-aperture;

[0258] A second autofocusing module is used to perform autofocusing on each synthesized first-order sub-aperture based on a model or a phase gradient-based focusing algorithm;

[0259] The second synthesis module is used to synthesize each fully focused first-order sub-aperture into a single full-aperture SAR image.

[0260] Example 3:

[0261] An embodiment of the present invention provides a storage medium storing a computer program for SAR autofocusing with multi-level sub-aperture segmentation, wherein the computer program enables a computer to execute the SAR autofocusing method described in Example 1.

[0262] Example 4:

[0263] An embodiment of the present invention provides an electronic device, including:

[0264] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the programs including a method for executing the SAR autofocusing method as described in Example 1.

[0265] It can be understood that the SAR autofocusing system, storage medium and electronic device with multi-level sub-aperture segmentation provided in the embodiments of the present invention correspond to the SAR autofocusing method with multi-level sub-aperture segmentation provided in the embodiments of the present invention. The explanation, examples and beneficial effects of the relevant contents can refer to the corresponding parts in the synthetic SAR autofocusing method, and will not be repeated here.

[0266] In summary, compared with the existing technology, the present invention has the following beneficial effects:

[0267] In this embodiment of the present invention, raw SAR echo data is preprocessed to obtain a coarsely focused SAR image. The coarsely focused SAR image is then divided into frequency-domain subapertures to reduce image resolution and sensitivity to motion errors. A model-based or phase-gradient-based focusing algorithm is then employed at each subaperture level to achieve high-quality images at each subaperture level. By focusing the subapertures step by step, global focusing of the SAR image is ultimately achieved. Compared to directly dividing the image into multiple subapertures, this method significantly improves SAR image focusing while increasing efficiency. This method has been effectively validated in simulations, actual airborne flights, and satellite-borne data.

[0268] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0269] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A SAR autofocusing method with multi-level sub-aperture segmentation, characterized in that: include: Acquire and preprocess raw SAR echo data to obtain coarse-focused SAR images; Dividing the coarsely focused SAR image into a plurality of first-order sub-apertures in the azimuth frequency domain; moving the Doppler center of each of the first-order sub-apertures to zero frequency; Each first-order subaperture adjusted by the Doppler center is evenly divided into a number of second-order subapertures; Based on a model or a phase gradient-based focusing algorithm, each of the secondary sub-apertures is subjected to a self-focusing process; Resynthesize each secondary sub-aperture after self-focusing into the corresponding primary sub-aperture; Based on the model or phase gradient based focusing algorithm, each synthesized first-order sub-aperture is subjected to self-focusing processing; Each fully focused first-order sub-aperture is synthesized into a single full-aperture SAR image; Each Doppler-center-adjusted primary subaperture is evenly divided into at least two secondary subapertures, including: Performing an azimuth Fourier transform on each Doppler-center-adjusted first-order subaperture to evenly divide the effective Doppler bandwidth of the signal into N subbands in the azimuth frequency domain, which serve as N second-order subapertures; where N is a positive integer greater than or equal to 2; The step of performing self-focusing processing on each of the secondary sub-apertures comprises: Performing inverse Fourier transform on the N secondary sub-apertures along the azimuth direction to obtain N sub-aperture time domain images; Calculate the cross-correlation function between any pair of sub-aperture time domain images and obtain mutual functions; Searching for the peak point position corresponding to the cross-correlation function to obtain the offset between the sub-aperture time domain image pair; Based on the offset, construct an offset matrix; Construct a position offset matrix between any pair of sub-aperture images introduced by 2nd to Nth order phase errors; Solving polynomial coefficients of various orders corresponding to N-order phase errors based on the offset matrix and the position offset matrix; Based on the polynomial coefficients of each order, a compensation operation is performed to ensure that each of the secondary sub-apertures reaches an optimal focus state.

2. The SAR autofocusing method according to claim 1, wherein: The coarsely focused SAR image is divided into two first-level sub-apertures in the azimuth frequency domain, including: Multiplying the azimuth frequency domain signal of the coarsely focused SAR image with the initialized matched filter function to obtain a range Doppler signal; The range Doppler signal is processed by inverse fast Fourier transform, and its absolute value is taken to obtain left and right sub-aperture images respectively; Calculating the relative displacement between the left and right sub-aperture images; Calculating an azimuth frequency domain linear modulation rate error based on the relative displacement and the effective Doppler bandwidth; Based on the azimuth frequency domain chirp rate error, modifying the matched filter function, and repeating the above operation until the azimuth frequency domain chirp rate error meets a preset accuracy; The left and right sub-aperture images finally obtained are output as the two first-level sub-apertures.

3. The SAR autofocusing method according to claim 2, wherein: The calculation process of the azimuth frequency domain linear modulation rate error includes: Assume that the azimuth Doppler spectrum model of the coarse-focused SAR image is as follows: Where S is the azimuth spectrum after the ideal quadratic phase matching, f a is the azimuth frequency, B d is the Doppler bandwidth, j is the imaginary unit, Δk af is the azimuth frequency modulation error, rect(·) is the rectangular window function, and exp(·) is the exponential function with the natural constant as the base; Divide the azimuth into left and right sub-aperture images in the frequency domain: Among them, S1 and S2 are the azimuth spectra of the left and right sub-aperture images after the azimuth spectrum represents S division; The corresponding time domain expression is: Among them, s1(t a ) and s2(t a ) represent the time domain images corresponding to the left and right sub-aperture images respectively. The first term rect(·) in Equation (4) and Equation (5) realizes the envelope of the time domain signal. The relative displacement between the left and right sub-aperture images is: Based on the relationship between the azimuth linear modulation rate, relative displacement, and Doppler bandwidth, the linear modulation rate error in the azimuth frequency domain is obtained as: Where Δk af is the azimuth frequency domain linear modulation rate error, and Δt is the relative displacement.

4. The SAR autofocusing method according to claim 1, wherein: The calculation process of the polynomial coefficients of each order corresponding to the N-order phase error includes: Assume that the error phase contained in the frequency domain of any sub-aperture in the first-level sub-aperture is in the form of an N-order polynomial, excluding linear errors; the phase error model is: Among them, φ e is the phase error, B sd is the Doppler bandwidth corresponding to the first-order sub-aperture a k is the kth order phase error coefficient in the polynomial phase error model, is the azimuth frequency f a The kth power of , that is, the kth order phase error in the phase error model; Divide any sub-aperture in the first-level sub-aperture into N sub-apertures, and the width of the sub-aperture is The phase error within the i-th sub-aperture range is: Among them, φ i represents the phase error within the i-th sub-aperture, f ai is the center of the i-th sub-aperture, and the expression is: In the phase error model, through binomial decomposition, it can be seen that the model of the linear phase error component is: Among them, φ lin，i is the phase error φ within the i-th sub-aperture i The linear error component of is the center of the i-th sub-aperture f ai k-1 power; The offset Δ between any two subaperture images i and j i,j for: The above linear equations are expressed in matrix form, and the position offset matrix Δ is: Δ=δa (13) in D=[D 1,2 …D 1,N D 2,3 …D 2,N D 3,4 …D N-1,N ] T (14) <h2 style=";text-align:left;direction:ltr">a=[a2 a3 … a<h2 style=";text-align:left;direction:ltr"> N <h2 style=";text-align:left;direction:ltr"> ]<h2 style=";text-align:left;direction:ltr"> T <h2 style=";text-align:left;direction:ltr"> (15) Wherein, the superscript T indicates transposition; represents the position offset between the i-th and j-th subaperture images introduced by the k-th order phase error and is defined as follows: Then the solution of the polynomial error coefficient is approximately: a=δ -1 D (18) Among them, δ -1 is the pseudo-inverse matrix of the position offset matrix δ.

5. A SAR autofocusing system with multi-level sub-aperture segmentation, characterized in that: The SAR autofocusing method for performing the multi-level sub-aperture segmentation according to claim 1 comprises: An acquisition module is used to acquire and preprocess raw SAR echo data to obtain a coarse-focused SAR image; A first-level division module, configured to divide the coarsely focused SAR image into a plurality of first-level sub-apertures in the azimuth frequency domain; an adjustment module, configured to move the Doppler center of each of the first-level sub-apertures to zero frequency; A secondary division module is used to evenly divide each primary sub-aperture adjusted by the Doppler center into a number of secondary sub-apertures; A first autofocusing module is configured to perform autofocusing processing on each of the secondary sub-apertures based on a model or a phase gradient-based focusing algorithm; A first synthesis module is used to synthesize each secondary sub-aperture after self-focusing into a corresponding primary sub-aperture; A second autofocusing module is used to perform autofocusing on each synthesized first-order sub-aperture based on a model or a phase gradient-based focusing algorithm; The second synthesis module is used to synthesize each fully focused first-order sub-aperture into a single full-aperture SAR image.

6. A storage medium, characterized in that The computer stores a computer program for SAR autofocusing with multi-level sub-aperture segmentation, wherein the computer program enables a computer to execute the SAR autofocusing method according to any one of claims 1 to 4.

7. An electronic device, characterized in that: include: one or more processors; Memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the programs include instructions for executing the SAR autofocusing method according to any one of claims 1 to 4.

Images