Method, device and equipment for correcting residual range migration of synthetic aperture radar images

Abstract

The present invention provides a method for correcting residual range motion of synthetic aperture radar images, which can be applied to the field of synthetic aperture radar imaging self-aggregation technology. The method includes: in response to determining that there is pixel offset in the image to be processed, preprocessing the image to be processed to obtain an initial image corresponding to the image to be processed; dividing the initial image to obtain multiple initial sub-images; calculating the autocorrelation normalized cross-power spectra corresponding to the multiple initial sub-images to obtain initial pixel offset data corresponding to the multiple initial sub-images; generating target pixel offset data based on noise data of the initial pixel offset data corresponding to the multiple initial sub-images; obtaining residual range motion corresponding to the initial image according to the target pixel offset data; and performing residual range motion correction on the initial image to obtain a corrected image corresponding to the initial image. The present invention also provides a method, apparatus and device for correcting residual range motion of synthetic aperture radar images.

Description

Technical Field

[0001] The present invention relates to the field of synthetic aperture radar imaging self-aggregation technology, and more specifically to a method, device and equipment for correcting residual range migration of synthetic aperture radar images. Background Art

[0002] Synthetic Aperture Radar (SAR) has the ability to work around the clock and in all weather conditions and is widely used in military reconnaissance, terrain mapping, environmental monitoring and other fields.

[0003] In the process of implementing the concept of the present invention, the inventors found that the echo image of the synthetic aperture radar still has defocusing after motion compensation, resulting in a problem of low imaging quality. Summary of the invention

[0004] In view of the above problems, the present invention provides a method and device for correcting residual range migration of synthetic aperture radar images.

[0005] According to a first aspect of the present invention, a residual range motion correction method for a synthetic aperture radar image is provided, comprising: in response to determining that a pixel offset exists in an image to be processed, preprocessing the image to be processed to obtain an initial image corresponding to the image to be processed, wherein the image to be processed includes azimuth data and range data, and the preprocessing includes range pulse compression processing and preliminary geometric correction processing; dividing the initial image based on the azimuth data and the range data to obtain a plurality of initial sub-images; calculating autocorrelation normalized cross power spectra corresponding to the plurality of initial sub-images to obtain initial pixel offset data corresponding to the plurality of initial sub-images; calculating noise data of the initial pixel offset data corresponding to the plurality of initial sub-images, and generating target pixel offset data based on the noise data of the initial pixel offset data corresponding to the plurality of initial sub-images; obtaining a residual range motion amount corresponding to the initial image according to the target pixel offset data; and performing residual range motion correction on the initial image according to the residual range migration amount corresponding to the initial image to obtain a corrected image corresponding to the initial image.

[0006] According to the embodiment of the present invention, there are overlapping areas between the multiple initial sub-images in azimuth and distance.

[0007] According to an embodiment of the present invention, the lengths of the multiple initial sub-images in the range direction are equal, and the lengths in the azimuth direction are equal.

[0008] According to an embodiment of the present invention, autocorrelation normalized cross-power spectra corresponding to a plurality of initial sub-images are calculated to obtain initial pixel offset data corresponding to the plurality of initial sub-images, including: calculating autocorrelation normalized cross-power spectra corresponding to the plurality of initial sub-images; performing unwrapping processing on the phases of the autocorrelation normalized cross-power spectra to obtain linear phases of the plurality of initial sub-images; and fitting the linear phases of the plurality of initial sub-images using the least squares method to obtain initial pixel offset data corresponding to the plurality of initial sub-images.

[0009] According to an embodiment of the present invention, noise data of initial pixel offset data corresponding to a plurality of initial sub-images is calculated, and target pixel offset data is generated based on the noise data of the initial pixel offset data corresponding to the plurality of initial sub-images, including: performing sliding average processing on the initial pixel offset data corresponding to the plurality of initial sub-images according to the initial pixel offset data corresponding to the plurality of initial sub-images to obtain sliding average data corresponding to the plurality of initial pixel offset data; obtaining noise data of the initial pixel offset data according to a standard deviation between the initial pixel offset data corresponding to the plurality of initial sub-images and the sliding average data; screening the initial pixel offset data with the smallest noise data in the same azimuth to obtain target pixel offset sub-data; and splicing the target pixel offset sub-data to generate target pixel offset data.

[0010] According to an embodiment of the present invention, the residual distance migration amount corresponding to the initial image is obtained according to the target pixel offset data, including: superimposing the target pixel offset sub-data to obtain the target pixel offset data; and obtaining the residual distance migration amount corresponding to the initial image according to the target pixel offset data.

[0011] According to an embodiment of the present invention, the method further comprises: performing azimuth phase error compensation on the corrected image to obtain a compensated image.

[0012] According to an embodiment of the present invention, the method further comprises: using a phase gradient autofocusing algorithm to perform azimuth phase error compensation on the compensation image to obtain a focused image.

[0013] A second aspect of the present invention provides a residual range motion correction device for synthetic aperture radar images, comprising: a processing module, for preprocessing the image to be processed in response to determining that there is a pixel offset in the image to be processed, to obtain an initial image corresponding to the image to be processed, wherein the image to be processed includes azimuth data and range data, and the preprocessing includes range pulse compression processing and preliminary geometric correction processing; a division module, for dividing the initial image based on the azimuth data and the range data to obtain a plurality of initial sub-images; a calculation module, for calculating autocorrelation normalized cross power spectra corresponding to the plurality of initial sub-images to obtain initial pixel offset data corresponding to the plurality of initial sub-images; a generation module, for calculating noise data of the initial pixel offset data corresponding to the plurality of initial sub-images, and generating target pixel offset data based on the noise data of the initial pixel offset data corresponding to the plurality of initial sub-images; an acquisition module, for obtaining a residual range motion amount corresponding to the initial image according to the target pixel offset data; and a correction module, for performing residual range motion correction on the initial image according to the residual range migration amount corresponding to the initial image to obtain a corrected image corresponding to the initial image.

[0014] A third aspect of the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-mentioned synthetic aperture radar image residual range migration correction method.

[0015] According to the residual range migration correction method, device and electronic device of synthetic aperture radar image provided by the present invention, the initial image corresponding to the image to be processed obtained by preprocessing is divided into blocks in azimuth and range directions to obtain multiple initial sub-images and calculate the initial pixel offset data corresponding to the multiple initial sub-images, and the target pixel offset data is generated based on the noise level of the initial pixel offset data corresponding to the multiple initial sub-images to obtain the residual range migration amount corresponding to the initial image, and the residual range migration correction is performed on the SAR initial image according to the residual range migration amount to obtain a high-quality SAR image. Since the residual range migration amount is calculated according to the autocorrelation normalized cross power spectrum, it is not necessary to estimate the residual range migration amount using sub-blocks with high signal-to-noise ratio, that is, the large amount of calculation caused by iteration and interpolation operations is avoided, and the imaging quality and robustness of SAR are improved to a certain extent. At the same time, since the computing power of the computer is fully utilized, it can be conveniently deployed on a computing platform such as a field programmable gate array (Field Programmable Gate Array, referred to as FPGA) or a graphics processing unit (Graphics Processing Unit, referred to as GPU). BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above contents and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0017] Figure 1 A diagram showing an application scenario of a method for correcting residual range migration of synthetic aperture radar images according to an embodiment of the present invention;

[0018] Figure 2 A flow chart of a method for correcting residual range motion of a synthetic aperture radar image according to an embodiment of the present invention is shown;

[0019] Figure 3A A schematic diagram showing the NCPS folded phase and the ANCPS folded phase of two time-shifted signals before unwrapping according to an embodiment of the present invention is shown;

[0020] Figure 3B A schematic diagram showing the NCPS phase and the ANCPS phase of two time-shifted signals after de-wrapping according to an embodiment of the present invention is shown;

[0021] Figure 3C The embodiment according to the present invention is shown Figure 3B Schematic diagram of the corresponding NCPS phase and ANCPS phase;

[0022] Figure 4A A schematic diagram showing an image before correction according to an embodiment of the present invention is shown;

[0023] Figure 4B A schematic diagram showing an image in an ideal state according to an embodiment of the present invention;

[0024] Figure 4C A rectified image according to an embodiment of the present invention is shown.

[0025] Figure 5 A schematic diagram showing dividing an initial image into blocks according to an embodiment of the present invention is shown;

[0026] Figure 6 A schematic diagram showing confirmation of target pixel offset sub-data according to an embodiment of the present invention is shown;

[0027] Figure 7 A schematic diagram showing the splicing of target pixel offset sub-data to obtain target pixel offset data according to an embodiment of the present invention;

[0028] Fig. 8A A synthetic aperture radar image without compensation and correction according to an embodiment of the present invention is shown;

[0029] Figure 8B shows a synthetic aperture radar image obtained under an ideal condition according to an embodiment of the present invention;

[0030] Figure 8C shows a focused image according to an embodiment of the present invention;

[0031] Fig. 9 A structural block diagram of a synthetic aperture radar image residual range migration correction device according to an embodiment of the present invention is shown; and

[0032] Fig.10 A block diagram of an electronic device suitable for implementing a method for correcting residual range migration of synthetic aperture radar images according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0033] Below, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of concepts of the present invention.

[0034] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the existence of features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0035] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0036] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0037] In the technical solution of the present invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0038] Ideally, the strip SAR imaging algorithm assumes that the SAR payload moves in a straight line, but in actual work, due to the influence of atmospheric turbulence and the limited control level of the flight platform, SAR will have a certain trajectory deviation. Traditional airborne platforms will be equipped with global navigation satellite systems and inertial orientation positioning navigation systems to measure motion errors, but due to the cost or payload weight and volume control, some SAR payload platforms cannot carry high-precision navigation systems.

[0039] Therefore, even after motion compensation of the synthetic aperture radar echo signal, there are still residual range migration of several range units, which makes the echo image distorted. The energy of the point target cannot be concentrated in the same range gate, resulting in the inability to well concentrate the energy in azimuth through pulse compression. Therefore, it is necessary to consider not only the phase error in azimuth but also the residual range migration.

[0040] Traditional cross-range gate correction technology often selects the initial sub-image with the highest signal-to-noise ratio through a sliding window, and searches and estimates the distance migration of each initial sub-image based on the non-parametric minimum entropy principle. In order to improve the estimation accuracy, it is necessary to upsample the data interpolation, which makes the calculation too large and is not conducive to the realization of real-time high-precision correction. In addition, the calculation of the signal-to-noise ratio of the initial sub-image requires the determination of the location of the target area of ​​interest in the initial sub-image. For the initial sub-images of different scenes, the definition of "target of interest" is inconsistent, and additional complex calculations are required to determine the location of the "target of interest". At the same time, the initial sub-image with a high signal-to-noise ratio may not be able to better reflect the residual distance migration of the initial sub-image. The search for the residual distance migration through the non-parametric minimum entropy principle is also uncertain in terms of the calculation amount and convergence for different scenes, which is not conducive to engineering application.

[0041] Based on this, the inventors found that the echo image of the synthetic aperture radar still has defocusing after motion compensation, resulting in a problem of low imaging quality, and the existing technology cannot solve this problem well.

[0042] In view of this, an embodiment of the present invention provides a method for correcting residual range motion of a synthetic aperture radar image, comprising: in response to determining that a pixel offset exists in an image to be processed, preprocessing the image to be processed to obtain an initial image corresponding to the image to be processed, wherein the image to be processed includes azimuth data and range data, and the preprocessing includes range pulse compression processing and preliminary geometric correction processing; dividing the initial image based on the azimuth data and the range data to obtain a plurality of initial sub-images; calculating autocorrelation normalized cross power spectra corresponding to the plurality of initial sub-images to obtain initial pixel offset data corresponding to the plurality of initial sub-images; calculating noise data of the initial pixel offset data corresponding to the plurality of initial sub-images, and generating target pixel offset data based on the noise data of the initial pixel offset data corresponding to the plurality of initial sub-images; obtaining a residual range motion amount corresponding to the initial image according to the target pixel offset data; and performing residual range motion correction on the initial image according to the residual range migration amount corresponding to the initial image to obtain a corrected image corresponding to the initial image.

[0043] Figure 1 A diagram showing an application scenario of a synthetic aperture radar image residual range migration correction method according to an embodiment of the present invention is shown.

[0044] like Figure 1 As shown, in the application scenario 100 of this embodiment, in the airborne synthetic aperture radar working platform 120, take the airborne synthetic aperture radar 120 (1) in the strip mode working state as an example. At this time, the running speed of the aircraft is V. Due to the influence of atmospheric turbulence and the limited control level of the flight platform, the actual trajectory 120 (2) of the airborne synthetic aperture radar 120 (1) is not a horizontal straight line. The ideal trajectory 120 (3) is represented by a dotted line. There is an arbitrary target point P (X0, Y0, Z0) in the imaging area 120 (4) of the airborne synthetic aperture radar 120 (1).

[0045] For the ideal trajectory, the closest slant distance from the airborne synthetic aperture radar to point P is r0, and for the actual operating trajectory at any time, the instantaneous slant distance from the airborne synthetic aperture radar 130 to point P is R(η), and for the instantaneous slant distance R0 of the ideal trajectory, there is a slant distance error ΔR(η) between R0 and R(η), which causes the imaging of the synthetic aperture radar to be defocused.

[0046] The server 110 may be a server that provides various services and can interact with the airborne synthetic aperture radar working platform 120. For example, the server 110 may be used to receive data, information, etc. from the airborne synthetic aperture radar working platform 120. Specifically, in response to determining that the image to be processed has pixel offset, the image to be processed may be preprocessed to obtain an initial image corresponding to the image to be processed, the initial image may be divided based on the azimuth data and the range data to obtain a plurality of initial sub-images, the autocorrelation normalized cross-power spectra corresponding to the plurality of initial sub-images may be calculated to obtain initial pixel offset data corresponding to the plurality of initial sub-images, the noise data of the initial pixel offset data corresponding to the plurality of initial sub-images may be calculated, and the target pixel offset data may be generated based on the noise data of the initial pixel offset data corresponding to the plurality of initial sub-images, and the residual range migration amount corresponding to the initial image may be obtained according to the target pixel offset data. According to the residual range migration amount corresponding to the initial image, the residual range migration correction may be performed on the initial image to obtain a corrected image corresponding to the initial image.

[0047] It should be noted that the residual range migration correction method for synthetic aperture radar images provided in the embodiment of the present invention can generally be executed by the server 110. Accordingly, the residual range migration correction device for synthetic aperture radar images provided in the embodiment of the present invention can generally be set in the server 110. The residual range migration correction method for synthetic aperture radar images provided in the embodiment of the present invention can also be executed by a server or server cluster that is different from the server 110 and can communicate with the server 110. Accordingly, the residual range migration correction device for synthetic aperture radar images provided in the embodiment of the present invention can also be set in a server or server cluster that is different from the server 110 and can communicate with the server 110.

[0048] It should be understood that Figure 1 The number of airborne synthetic aperture radars and servers in the embodiment is only for illustration. Any number of airborne synthetic aperture radars and servers may be provided according to implementation requirements.

[0049] According to an embodiment of the present invention, the motion trajectory S of the airborne synthetic aperture radar at a running speed V can be expressed as the following formula (1).

[0050] (1).

[0051] Among them, η is used to represent the slow time, Δx(η) is used to represent the flight direction position offset, Δy(η) is used to represent the radial offset, H is used to represent the ideal flight altitude, and Δz(η) is used to represent the altitude offset.

[0052] According to an embodiment of the present invention, for any target point P (X0, Y0, Z0), the instantaneous slant range R(η) between the airborne synthetic aperture radar 130 and the point P can be expressed by the following formula (2).

[0053] (2).

[0054] Among them, X0 is used to represent the azimuth coordinate of point P, Y0 is used to represent the distance coordinate of point P, and Z0 is used to represent the altitude coordinate of point P.

[0055] According to an embodiment of the present invention, the shortest slant distance from the airborne synthetic aperture radar 130 to the point P is r0, which can be expressed as the following formula (3).

[0056] (3).

[0057] According to an embodiment of the present invention, the slant range error ΔR(η) can be expressed as the following formula (4).

[0058] (4).

[0059] Wherein, β is used to represent the angle between the direction corresponding to the closest slant range r0 of the airborne synthetic aperture radar 130 and the vertical to the ground. The sine relationship between the closest slant range r0 and the range coordinate of P is shown in the following formula (5), and the cosine relationship between the closest slant range r0 and the height coordinate of P is shown in the following formula (6).

[0060] (5).

[0061] (6).

[0062] According to an embodiment of the present invention, the echo signal S of the airborne synthetic aperture radar can be obtained based on the basic principle of synthetic aperture radar. echo (τ,η), expressed as follows:

[0063] (7).

[0064] Among them, τ is used to represent fast time, A0 is used to represent any complex constant, and w r The window function used to represent the distance direction, w a is used to represent the window function of the azimuth, λ is used to represent the wavelength of the transmitted signal, c is used to represent the speed of light, j is used to represent the imaginary unit, and K r Used to indicate the signal distance modulation frequency.

[0065] According to an embodiment of the present invention, the echo signal S echo(τ,η) can be used to perform pulse compression in the range direction and preliminary geometric correction to obtain a range pulse compression signal S0(τ,η). Due to the arbitrary complex constants, the window function in the range direction and the window function in the azimuth direction, the echo signal S echo The influence of (τ, η) is small, so it is omitted in the following formula. The distance pulse pressure signal S0(τ, η) can be expressed by the following formula (8).

[0066] (8).

[0067] Among them, B r Used to indicate the transmit pulse bandwidth.

[0068] According to an embodiment of the present invention, when the slant range error ΔR(η) satisfies the following formula (9), the residual range migration amount will cross the range gate, that is, the image of the range pulse pressure signal S0(τ,η) will be distorted, that is, the energy of each target point cannot be concentrated in the same range gate.

[0069] (9).

[0070] Among them, f s Used to indicate the sampling rate in the distance direction.

[0071] According to an embodiment of the present invention, the flight direction position offset Δx(η) is determined by the speed deviation in the direction of the aircraft. Under normal circumstances, the flight direction position offset Δx(η) is smaller than the radial offset Δy(η) and the elevation offset Δz(η). After preliminary motion compensation by a low-precision navigation system, the flight direction position offset Δx(η) can be further reduced. At the same time, the difference between Vη and the azimuth coordinate X0 of point P is the synthetic aperture length L. s , synthetic aperture length L s The maximum value of the ratio to the nearest slant distance r0 satisfies the following formula (10).

[0072] (10).

[0073] Among them, θ α Used to indicate the beamwidth in azimuth.

[0074] According to an embodiment of the present invention, θ α The product of Δx(η) generally satisfies the following formula (11).

[0075] (11).

[0076] According to an embodiment of the present invention, combined with formula (4), it can be known that the first term of the slant range error ΔR(η) can be ignored, that is, the value of the slant range error ΔR(η) is determined by β. For the same scene, when the lower viewing angles of the near end and the far end do not change much, it can be approximately considered that sinβ remains unchanged, and the target viewing angle at the center of the imaging area is used as the standard. That is, for the same scene, the slant range error ΔR(η) can be approximately considered to remain unchanged for imaging points at different positions. As long as the above conditions are met, the slant range error ΔR(η) does not change with the operating distance of the synthetic aperture radar. Therefore, it is only necessary to accurately estimate the slant range error ΔR(η) and uniformly compensate it based on the echo signal of the same scene to achieve the correction of the residual range migration.

[0077] The following will be based on Figure 1 The scene described by Figure 2~Figure 8C The residual range migration correction method for synthetic aperture radar images according to an embodiment of the present invention is described in detail.

[0078] Figure 2 A flow chart of a method for correcting residual range motion of a synthetic aperture radar image according to an embodiment of the present invention is shown.

[0079] like Figure 2 As shown, the embodiment 200 includes operations S210 to S260.

[0080] In operation S210, in response to determining that there is a pixel offset in the image to be processed, the image to be processed is preprocessed to obtain an initial image corresponding to the image to be processed.

[0081] According to an embodiment of the present invention, the essence of pixel offset is that the signals at each point have a time delay, so that the energy of the point target cannot be gathered at the same range gate, and the energy in the azimuth direction cannot be well gathered through pulse compression, resulting in distortion of the image of the synthetic aperture radar.

[0082] According to an embodiment of the present invention, preprocessing includes performing pulse compression in the range direction and performing preliminary geometric correction on the image to be processed. Among them, pulse compression technology can improve the detection distance and ensure high resolution when the radar's transmission power is limited. Pulse compression in the range direction can be achieved through a matched filter. Linear frequency modulation technology can be used to perform pulse compression in the range direction, so that the entire pulse width of the corresponding signal of the image to be processed is effectively reduced, and the amplitude is greatly improved. An improved Chirp Scaling algorithm (CSA) can be used to perform geometric correction of the preliminary residual range migration amount on the image to be processed. CSA can adapt well to the correction of motion errors.

[0083] According to an embodiment of the present invention, the image to be processed includes azimuth data and range data. The azimuth data is used to represent the signal component of the image to be processed in the azimuth direction, and the range data is used to represent the signal component of the image to be processed in the range direction.

[0084] In operation S220, the initial image is divided based on the azimuth data and the range data to obtain a plurality of initial sub-images.

[0085] According to an embodiment of the present invention, the initial image is divided into two-way blocks in the azimuth direction and the distance direction.

[0086] For example: the initial image orientation can be divided into k N blocks, each block is N0 long, and the distance is divided into k M , each block is M0 long, and the length of each initial sub-image in the range and azimuth directions is an even unit.

[0087] In operation S230, autocorrelation normalized cross power spectra corresponding to the plurality of initial sub-images are calculated to obtain initial pixel offset data corresponding to the plurality of initial sub-images.

[0088] According to an embodiment of the present invention, an autocorrelated normalized cross-power spectrum (ANCPS) is obtained by performing an autocorrelation operation on two signals with time delay or pixel offset, and the linear phase difference between the two signals can be obtained according to the ANCPS.

[0089] According to an embodiment of the present invention, based on the properties of discrete Fourier transform, in order to compensate for pixel offset, when moving in the time domain, it is equivalent to adding a linear phase in the frequency domain. However, for the actual working state of SAR, an additional noise phase will be introduced, so the linear phase must be accurately estimated, that is, a straight line fitting is required. However, in fact, due to the existence of the noise phase, errors will occur when the linear is unwrapped, and a relatively ideal straight line cannot be obtained. Therefore, the linear phase must be denoised, and the autocorrelation normalized cross power spectrum is to remove the noise phase. At the same time, for every unit change in the slope of the linear phase added in the frequency domain, the signal sequence corresponding to the initial sub-image will shift by a unit pixel point. Therefore, ANCPS can be used to obtain accurate pixel offset data corresponding to multiple initial sub-images.

[0090] In operation S240, noise data of initial pixel offset data corresponding to the plurality of initial sub-images is calculated, and target pixel offset data is generated based on the noise data of the initial pixel offset data corresponding to the plurality of initial sub-images.

[0091] According to an embodiment of the present invention, the pixel offset data reflects the noise level of the image to a certain extent. Therefore, the pixel offset data corresponding to the multiple initial sub-images can be calculated based on the pixel offset data corresponding to the multiple initial sub-images. The higher the pixel offset data, the greater the corresponding noise data.

[0092] According to an embodiment of the present invention, part of the valid pixel offset data may be screened according to the noise data of the pixel offset data corresponding to each initial sub-image to generate the target pixel offset data.

[0093] In operation S250, a residual distance migration amount corresponding to the initial image is obtained according to the target pixel offset data.

[0094] According to an embodiment of the present invention, the residual distance migration is used to represent the data of the distance deviation caused by the pixel point offset. The initial image obtained by the preprocessing of the image to be processed shows an arc, which will lead to poor image quality after the subsequent azimuth pulse compression. Therefore, it is necessary to calculate the residual distance migration corresponding to the initial image and correct it to straighten the arc.

[0095] In operation S260, residual distance migration correction is performed on the initial image according to the residual distance migration amount corresponding to the initial image to obtain a corrected image corresponding to the initial image.

[0096] According to an embodiment of the present invention, when aligning two time-delayed signals, it is necessary to correct the residual distance migration, that is, the residual distance migration corresponding to the target image is regarded as the residual distance migration of the image to be processed, and there is no need to select the initial sub-image with the highest signal-to-noise ratio for estimation, thereby reducing a certain amount of calculation. At the same time, sub-pixel level time delay compensation can be achieved without interpolation operation, which greatly reduces the impact of time delay on the compensated image and improves the image quality.

[0097] According to the residual range migration correction method and device of synthetic aperture radar image provided by the present invention, the initial image corresponding to the image to be processed obtained by preprocessing is divided into blocks in azimuth and range directions to obtain multiple initial sub-images and calculate the initial pixel offset data corresponding to the multiple initial sub-images, and the target pixel offset data is generated based on the noise level of the initial pixel offset data corresponding to the multiple initial sub-images to obtain the residual range migration amount corresponding to the initial image, and the residual range migration correction is performed on the SAR initial image according to the residual range migration amount to obtain a high-quality SAR image. Since the residual range migration amount is calculated according to the autocorrelation normalized cross power spectrum, it is not necessary to estimate the residual range migration amount using sub-blocks with high signal-to-noise ratio, that is, the large amount of calculation caused by iteration and interpolation operations is avoided, and the imaging quality and robustness of SAR are improved to a certain extent. At the same time, since the computing power of the computer is fully utilized, it can be conveniently deployed on a computing platform such as a field programmable gate array (Field Programmable Gate Array, referred to as FPGA) or a graphics processing unit (Graphics Processing Unit, referred to as GPU).

[0098] With respect to the above operation S210, the above formulas (7) and (8) can be combined, and the process of preprocessing a target point signal in the image to be processed can be expressed as the following formula (12).

[0099] (12).

[0100] Among them, S0(n,m) is used to represent the preprocessed signal of any target point, n is the azimuth index of any target point, and m is the distance index of any target point.

[0101] According to an embodiment of the present invention, the azimuth index n of any target point satisfies the following formula (13).

[0102] (13).

[0103] Where N is the number of pulses.

[0104] According to an embodiment of the present invention, the distance index m of any target point satisfies the following formula (14).

[0105] (14).

[0106] Where M is the number of pixels for each pulse.

[0107] According to an embodiment of the present invention, N and M are both integers greater than 1, n is an integer greater than or equal to 1 and less than or equal to N, and m is an integer greater than or equal to 1 and less than or equal to M. N and M can be selected according to actual conditions and are not limited here. For example, N can be 10000, 30000 or 50000, etc., and M can be 20000, 60000 or 100000, etc.

[0108] According to an embodiment of the present invention, the radar echo signal of the same scene can be regarded as the superposition of the echo signals of all target points in the scene. Since all target points approximately share the same slant range error ΔR(η), the initial image S(n,m) corresponding to the image to be processed can be expressed as the following formula (15).

[0109] (15).

[0110] The initial image S(n,m) includes azimuth data and distance data.

[0111] Regarding the above operation S230 , in order to better understand the autocorrelation operation, the calculation process of ANCPS is now described by taking two time-shifted signals S1 (τ) and S2 (τ) as an example.

[0112] According to an embodiment of the present invention, the signal S1(τ) and the signal S2(τ) satisfy the following formula (16).

[0113] (16).

[0114] Wherein, τ0 is the time delay of signal S1(τ) relative to signal S2(τ).

[0115] According to an embodiment of the present invention, the Fourier transform F1(ω) of the signal S1(τ) and the Fourier transform F2(ω) of the signal S2(τ) satisfy the following formula (17).

[0116] (17).

[0117] Where H(ω) is the linear phase, N P (ω) is the phase of the noise term generated by the Gaussian white noise sequence. Approximately, F1(ω) has one more linear phase and one more noise phase relative to F2(ω). H(ω) and N P (ω) can be expressed as the following formula (18).

[0118] (18).

[0119] Where ω is the frequency, is a Gaussian white noise sequence about ω, and φ0 is used to represent the phase error in the constant term.

[0120] According to an embodiment of the present invention, if one wants to align the signal S1(τ) and the signal S2(τ) in time, that is, to eliminate the time delay of τ0, the difference in their linear phases in the frequency domain can be estimated and compensated in the frequency domain. P The existence of (ω) will bring about a large deviation in phase unwrapping, and cannot estimate the linear phase difference in the frequency domain well. Therefore, the autocorrelation normalized cross power spectrum is introduced to estimate the linear phase difference.

[0121] According to an embodiment of the present invention, the normalized cross-power spectrum (hereinafter referred to as NCPS) of the signal S1(τ) and the signal S2(τ) is It can be expressed as the following formula (19).

[0122] (19).

[0123] in, Denotes complex conjugate.

[0124] According to an embodiment of the present invention, by substituting the above formula (17) into formula (19), the following expression (20) can be obtained.

[0125] (20).

[0126] According to the embodiment of the present invention, when the constant term phase error φ0 in the linear phase H(ω) is ignored, the ideal linear phase H(ω) satisfies the formula (21).

[0127] (twenty one).

[0128] Where u is the offset of the frequency ω.

[0129] According to an embodiment of the present invention, ideally, the phase of the ideal NCPS between the two signals S1(τ) and S2(τ) satisfying the condition of formula (16) is a straight line about the frequency ω plus a section of Gaussian white noise. According to the properties of Fourier transform, when moving in the time domain, it is equivalent to adding a linear phase in the frequency domain. If directly If the phase of is used as the compensation, additional noise phase will be introduced, so H(ω) must be accurately estimated. However, in the actual work of airborne SAR, due to the existence of noise phase, When the phase is unwrapped, a certain error will occur and a relatively ideal straight line cannot be obtained. Therefore, it is necessary to use ANCPS to The phase is denoised.

[0130] According to an embodiment of the present invention, by performing an autocorrelation operation on the above formula (20), the autocorrelation normalized cross power spectrum in the following formula (22) can be obtained: .

[0131] (twenty two).

[0132] According to an embodiment of the present invention, the normalized cross power spectrum of S1(τ) and S2(τ) is Autocorrelation normalized cross power spectrum with S1(τ) and S2(τ) The relationship is as follows: formula (23).

[0133] (twenty three).

[0134] Among them, IFFT {} is the inverse Fourier transform operation, and FFT {} is the Fourier transform.

[0135] According to an embodiment of the present invention, by substituting formula (20) and formula (21) into formula (22), the following formula (24) can be obtained.

[0136] (twenty four).

[0137] Among them, the expression in the square brackets is the autocorrelation of the Gaussian noise signal, and the Gaussian white noise signal after autocorrelation is a signal with σ at the origin. 2 The noise energy will be compressed to one point, thus indirectly achieving the purpose of denoising. With the complex conjugate H of the ideal NCPS * (ω) are almost equivalent, so we only need to The phase of the ideal NCPS can be approximately obtained by performing phase extraction and unwrapping.

[0138] According to an embodiment of the present invention, in order to quickly obtain ANCPS, according to the properties of convolution, it can be obtained by using the Fourier transform in the frequency domain complex conjugate multiplication method. According to the properties of discrete Fourier transform, the slope of the added linear phase in the frequency domain will shift one pixel to the right for every unit slope change, so the pixel offset data corresponding to multiple initial sub-images can be obtained through ANCPS.

[0139] Figure 3A A schematic diagram showing the NCPS folding phase and the ANCPS folding phase of two time-shifted signals before dewrapping according to an embodiment of the present invention is shown.

[0140] Figure 3BA schematic diagram showing the NCPS phase and the ANCPS phase of two time-shifted signals after de-entanglement according to an embodiment of the present invention is shown.

[0141] Figure 3C The embodiment according to the present invention is shown Figure 3B Schematic diagram of the corresponding NCPS phase and ANCPS phase.

[0142] according to FIG. 3A to FIG. 3C It can be seen that after NCPS is autocorrelated to obtain ANCPS, the normalized cross power spectrum phase noise is significantly removed. Figure 3B and Figure 3C It can be seen that an obvious straight line can be observed in the ANCPS phase after unwinding.

[0143] With respect to the above operation S240, for each initial sub-image, the point located in the middle in both the azimuth and the distance directions is the center point, and the azimuth index of the center point of the i-th initial sub-image in the azimuth direction and the j-th initial sub-image in the distance direction is n. i , the distance index is n j The center point can satisfy the following condition of formula (25).

[0144] (25).

[0145] Among them, S i,j (n,m) is used to represent the center point of the jth initial sub-image at the ith distance upward in the azimuth direction. , and n and m satisfy the conditions of the following formula (26).

[0146] (26).

[0147] Among them, N0 is the azimuth upward length of the initial sub-image, and M0 is the distance upward length of the initial sub-image.

[0148] According to the embodiment of the present invention, in each initial sub-image, there exists a relationship as shown in formula (27) between the signals of each point in the azimuth direction and the center point.

[0149] (27).

[0150] in, It is used to represent the pixel offset data of the signals of each point in the azimuth direction relative to the center point signal in multiple initial sub-images. As mentioned above, time delay will cause the offset of the pixel points. with time-delayed data.

[0151] According to an embodiment of the present invention, formula (28) shows that the ANCPS is used to calculate .

[0152] (28).

[0153] Among them, ANCPS pix {} is used to obtain pixel offset data.

[0154] According to the embodiment of the present invention, after bidirectional block division, the obtained ΔR(n) should change continuously and slowly, that is, The corresponding curve should be a continuous and slow change. For the initial sub-images with the same i and different j, the obtained In theory, they should be consistent. In other words, for the same azimuth time, the residual range migration of images from different range gates should be consistent. However, in actual situations, the initial sub-images that satisfy the consistent azimuth index but inconsistent range index correspond to inconsistent ground features, and cannot be solved correctly when using ANCPS. A certain degree of noise will appear, causing the curve corresponding to the pixel offset data to be distorted. Therefore, it is necessary to calculate the noise data of the pixel offset data corresponding to the multiple initial sub-images based on the pixel offset data corresponding to the multiple initial sub-images, and generate the target pixel offset data based on the noise data of the pixel offset data corresponding to the multiple initial sub-images.

[0155] With respect to the above operation S260, the process of performing residual range migration correction on the initial image S(n,m) can be shown in the following formula (29).

[0156] (29).

[0157] Among them, ANCPS CMP {} is used to represent the residual range migration correction, and Δr(n) is the pixel offset data of the entire initial image.

[0158] Figure 4A A schematic diagram showing an S(n,m) image before correction according to an embodiment of the present invention is shown.

[0159] Figure 4B A schematic diagram of an S(n,m) image in an ideal state according to an embodiment of the present invention is shown.

[0160] Figure 4C A rectified image according to an embodiment of the present invention is shown.

[0161] according to Figure 4A , Figure 4B and Figure 4CIt can be seen that, compared with the image to be processed before correction, the corrected image after residual range migration correction using the above embodiment 200 has the curve in the SAR image straightened, which is close to the effect under ideal conditions, that is, the quality of the image obtained by data compensation using a high-precision integrated navigation system is close.

[0162] According to the embodiment of the present invention, there are overlapping areas between the multiple initial sub-images in azimuth and distance.

[0163] According to an embodiment of the present invention, for the overlapping area of ​​the initial sub-images, the overlapping length in the azimuth direction is N. over , the overlap length in the distance upward is M over .

[0164] According to an embodiment of the present invention, the lengths of the multiple initial sub-images in the range direction are equal, and the lengths in the azimuth direction are equal.

[0165] According to the embodiment of the present invention, each initial sub-image has an equal size, but the image quality of each initial sub-image is inconsistent.

[0166] According to the embodiment of the present invention, dividing the initial image into initial sub-images of equal size can facilitate subsequent screening of pixel offset data corresponding to the initial image.

[0167] According to an embodiment of the present invention, the initial image is bidirectionally divided into blocks to obtain a plurality of initial sub-images of equal size and having overlapping areas, which are used to generate a target image according to the noise level of the pixel offset data corresponding to each initial image. There is no need to screen the initial sub-images based on the signal-to-noise ratio, which reduces the amount of calculation and improves the correction accuracy to a certain extent.

[0168] Figure 5 A schematic diagram of dividing an initial image into blocks according to an embodiment of the present invention is shown.

[0169] like Figure 5 As shown, the initial image 510 is bidirectionally cut in the azimuth and distance directions according to a predetermined length to obtain a plurality of initial sub-images 520 of equal size.

[0170] According to an embodiment of the present invention, autocorrelation normalized cross-power spectra corresponding to a plurality of initial sub-images are calculated to obtain initial pixel offset data corresponding to the plurality of initial sub-images, including: calculating autocorrelation normalized cross-power spectra corresponding to the plurality of initial sub-images; performing unwrapping processing on the phases of the autocorrelation normalized cross-power spectra to obtain linear phases of the plurality of initial sub-images; and fitting the linear phases of the plurality of initial sub-images using the least squares method to obtain initial pixel offset data corresponding to the plurality of initial sub-images.

[0171] According to an embodiment of the present invention, after the ANCPS of the initial sub-image is calculated, the process of extracting its phase and performing de-wrapping processing is as follows: Formula (30).

[0172] (30).

[0173] Among them, phase{} is used to represent taking the phase of a complex sequence and performing unwrapping processing. is the ANCPS of the initial sub-image, Φ(m) is The linear phase.

[0174] According to an embodiment of the present invention, the phase slope can be obtained by fitting Φ(m) using the least squares method according to formula (31).

[0175] (31).

[0176] Where k is the phase slope.

[0177] According to the embodiment of the present invention, pixel shift data may be determined based on the phase slope and the unit slope change.

[0178] According to an embodiment of the present invention, the unit slope change Δk can be obtained by the following formula (32).

[0179] (32).

[0180] Among them, the phase period is 2π.

[0181] According to the embodiment of the present invention, based on the time-shift property of discrete Fourier transform, when the slope of the linear phase added to the point signal sequence in the initial sub-image in the frequency domain changes by Δk, it will move one pixel to the right as a whole, that is, the time delay data generated is 1 / f s .

[0182] According to an embodiment of the present invention, the pixel offset data G can be obtained according to the following formula (33).

[0183] (33).

[0184] The pixel offset data G may be a decimal, which means that the pixel offset is not an integer number of pixels.

[0185] According to the embodiment of the present invention, for each initial sub-image, the pixel offset data of all point signals in the azimuth direction with respect to the central point signal are traversed to obtain the pixel offset data of each initial sub-image.

[0186] According to an embodiment of the present invention, the unit slope change is determined based on the number of pixels and the periodic phase of each initial sub-image; the pixel offset data is determined based on the phase slope and the unit slope change, and pixel offset data that is less than the total number of pixels can be determined, that is, the pixel offset at the sub-pixel level is determined.

[0187] According to an embodiment of the present invention, the phase slope reflects the pixel offset data between the signal sequence of each point in the azimuth direction and the center point signal in the initial sub-image. The signals are "aligned" in the time domain, and the linear phase is generated using the pixel offset data and compensated in the frequency domain. It is worth noting that since the pixel offset data is reflected in the slope of Φ(n,m), its resolution can be infinitely high in theory and is not limited by the sampling rate. Therefore, sub-pixel estimation and compensation can be achieved, and there is no interpolation or other operations that increase the amount of data and calculation.

[0188] According to an embodiment of the present invention, noise data of initial pixel offset data corresponding to a plurality of initial sub-images is calculated, and target pixel offset data is generated based on the noise data of the initial pixel offset data corresponding to the plurality of initial sub-images, including: performing sliding average processing on the initial pixel offset data corresponding to the plurality of initial sub-images according to the initial pixel offset data corresponding to the plurality of initial sub-images to obtain sliding average data corresponding to the plurality of initial pixel offset data; obtaining noise data of the initial pixel offset data according to a standard deviation between the initial pixel offset data corresponding to the plurality of initial sub-images and the sliding average data; screening the initial pixel offset data with the smallest noise data in the same azimuth to obtain target pixel offset sub-data; and splicing the target pixel offset sub-data to generate target pixel offset data.

[0189] According to an embodiment of the present invention, sliding average processing can represent an effective data processing and analysis tool, which eliminates accidental changes in data by calculating moving averages, reveals the development trend of data, and is used for prediction, interpolation of missing values, and smoothing and filtering data.

[0190] According to an embodiment of the present invention, the noise data can be calculated according to the following formula (34).

[0191] (34).

[0192] Among them, smooth{} is used to indicate the sliding average processing of the sequence, std{} is used to indicate the calculation of the standard deviation of two sequences, σ i,j Used to represent The noise level of the initial pixel offset data of the initial sub-image also reflects the noise level of the initial sub-image. The corresponding image "smoothness". i,jThe smaller it is, the smoother the image is and the smaller the noise level is. i,j The more it satisfies the target pixel offset sub-data.

[0193] According to the embodiment of the present invention, for the initial sub-image in the same azimuth, that is, for each initial sub-image with the same i but different j, there is an estimate of a section of optimal initial pixel offset data.

[0194] According to an embodiment of the present invention, the target pixel offset sub-data may be determined by the following formula (35).

[0195] (35).

[0196] Among them, Δr best-i (n) is the optimal initial pixel offset data in the same azimuth direction, that is, only the initial pixel offset data satisfying the above formula (35) is the target pixel offset sub-data.

[0197] Figure 6 A schematic diagram of confirming target pixel offset sub-data according to an embodiment of the present invention is shown.

[0198] like Figure 6 As shown, each initial pixel offset data 520 is screened to obtain the target pixel offset sub-data 610. It can be clearly seen that the target sub-image pixel offset sub-data is the most "smooth" initial pixel offset data with the smallest pixel offset in the same azimuth.

[0199] According to an embodiment of the present invention, after the target pixel offset sub-data are confirmed, the target pixel offset sub-data are spliced ​​to generate the target pixel offset data.

[0200] Figure 7 A schematic diagram showing splicing target pixel offset sub-data to obtain target pixel offset data according to an embodiment of the present invention is shown.

[0201] like Figure 7 As shown, the relatively smooth target pixel offset sub-data 610 obtained by screening are spliced ​​to obtain target pixel offset data 710 .

[0202] According to an embodiment of the present invention, the initial image is estimated by dividing the initial image into blocks. , using ANCPS to estimate the quality of the initial sub-image instead of screening the initial sub-image with high signal-to-clutter ratio is more robust, does not require iteration and interpolation operations, effectively reduces the amount of calculation, and at the same time, the estimation of pixel offset data is more accurate.

[0203] According to an embodiment of the present invention, obtaining the residual distance migration amount corresponding to the initial image according to the target pixel offset data includes superimposing the target pixel offset sub-data to obtain the target pixel offset data.

[0204] According to an embodiment of the present invention, a residual distance migration amount corresponding to an initial image is obtained according to the target pixel offset data.

[0205] According to an embodiment of the present invention, the process of obtaining target pixel offset data by superimposing target pixel offset sub-data is as follows: Formula (36).

[0206] (36).

[0207] Among them, U is the splicing operation on the target sub-image.

[0208] According to an embodiment of the present invention, when the initial image is divided into blocks, an overlapping portion is reserved in azimuth, and the constant term deviation of different target sub-images can be adjusted according to the deviation of the constant term of the overlapping portion, thereby achieving the purpose of curve segment splicing.

[0209] According to the embodiment of the present invention, since the upward unit of the distance S(n,m) is a pixel, the amount of pixel offset compensation in formula (29) is Δr(n).

[0210] According to an embodiment of the present invention, for formula (28), |S i,j (n i, m)|with|S i,j There is time delay data between (n,m)|, which causes pixel shift. |S i,j (n i, m)|with|S i,j (n,m)| It can be obtained by the following formula (37).

[0211] (37).

[0212] Among them, R bin is the pixel width of the distance upward, The unit of is consistent with the unit of the distance index m, which is the number of pixels, so it will cause the offset of pixels or sampling points, which is still time offset in essence.

[0213] According to an embodiment of the present invention, the residual distance migration amount ΔR(n) corresponding to the initial image can be obtained according to the following formula (38).

[0214] (38).

[0215] Wherein, C is a constant, which can be set to 0 in general.

[0216] According to an embodiment of the present invention, target pixel offset data, i.e., pixel offset data corresponding to an initial image, is obtained by superimposing target pixel offset sub-data, and based on this, the pixel offset data of a target image of a synthetic aperture radar is compensated to obtain a corrected image that eliminates residual range migration.

[0217] According to an embodiment of the present invention, in order to better explain the correction process of the above formula (29), two discrete signals are taken as an example and further explained through the following formulas (39) to (41).

[0218] According to an embodiment of the present invention, the second discrete signal S n2 (m) For the first discrete signal S n1 (m) There is a pixel offset.

[0219] According to an embodiment of the present invention, the first discrete signal S n1 (m) and the second discrete signal S n2 (m) is subjected to fast Fourier transform and the result is as follows:

[0220] (39).

[0221] According to an embodiment of the present invention, S can be obtained according to the following formula (40): n2 (m) relative to S n1 (m) The number of pixels offset P'.

[0222] (40).

[0223] According to an embodiment of the present invention, based on the known pixel offset data, S n2 (m) and S n1 (m) Alignment requires two Fourier transforms, and the corrected signal S' can be obtained according to the following formula (40): n2 (m).

[0224] (41).

[0225] Among them, F' n2 (m) is for S n2 The result obtained by Fourier transform of (m) is corrected, i is an imaginary unit, then S' n2 (m) relative to S n2 (m) Moved Pix(S n1 ,S n2 ) points, basically the same as S n1 (m) Alignment.

[0226] According to an embodiment of the present invention, the method further comprises: performing azimuth phase error compensation on the corrected image to obtain a compensated image.

[0227] According to an embodiment of the present invention, for a preprocessed signal S0(n,m) of any target point, the residual distance migration amount is corrected to obtain a corresponding corrected signal S'0(n,m) which can be expressed by the following formula (42).

[0228] (42).

[0229] According to an embodiment of the present invention, it is also necessary to perform azimuth phase error compensation on the corrected image S'0(n,m), and the obtained compensated image S''0(n,m) can be expressed by the following formula (43).

[0230] (43).

[0231] According to an embodiment of the present invention, the method further comprises: using a phase gradient autofocusing algorithm to perform azimuth phase error compensation on the compensation image to obtain a focused image.

[0232] According to an embodiment of the present invention, the compensated image obtained by compensating for the residual range migration and the azimuth phase error still has some uncompensated azimuth phase errors. The azimuth phase error can be compensated using a relatively mature phase gradient autofocusing algorithm to achieve complete focusing of the initial image.

[0233] Fig. 8A A synthetic aperture radar image without compensation and correction according to an embodiment of the present invention is shown.

[0234] Figure 8B The synthetic aperture radar image obtained under ideal conditions according to an embodiment of the present invention is shown.

[0235] Figure 8C A focused image according to an embodiment of the present invention is shown.

[0236] like Fig. 8A , Figure 8B and Figure 8C By comparison, it can be seen that the focusing effect of the focused image obtained by the above method is close to the imaging quality in the ideal state, and has a better effect.

[0237] Based on the above synthetic aperture radar image residual range migration correction method, the present invention also provides a synthetic aperture radar image residual range migration correction device. Fig. 9 The device is described in detail.

[0238] Fig. 9A structural block diagram of a synthetic aperture radar image residual range migration correction device according to an embodiment of the present invention is shown.

[0239] like Fig. 9 As shown, the synthetic aperture radar image residual range migration correction device 900 of this embodiment includes a processing module 910, a division module 920, a calculation module 930, a generation module 940, an acquisition module 950 and a correction module 960.

[0240] The processing module 910 is used to pre-process the image to be processed in response to determining that there is pixel offset in the image to be processed to obtain an initial image corresponding to the image to be processed. In one embodiment, the processing module 910 can be used to perform the operation S210 described above, which will not be repeated here.

[0241] The division module 920 is used to divide the initial image based on the azimuth data and the range data to obtain a plurality of initial sub-images. In one embodiment, the division module 920 can be used to perform the operation S220 described above, which will not be described in detail here.

[0242] The calculation module 930 is used to calculate the autocorrelation normalized cross power spectra corresponding to the multiple initial sub-images to obtain the initial pixel offset data corresponding to the multiple initial sub-images. In one embodiment, the calculation module 930 can be used to perform the operation S230 described above, which will not be described in detail here.

[0243] The generating module 940 is used to calculate the noise data of the initial pixel offset data corresponding to the multiple initial sub-images, and generate the target pixel offset data based on the noise data of the initial pixel offset data corresponding to the multiple initial sub-images. In one embodiment, the generating module 940 can be used to perform the operation S240 described above, which will not be repeated here.

[0244] The obtaining module 950 is used to obtain the residual distance migration amount corresponding to the initial image according to the target pixel offset data. In one embodiment, the obtaining module 920 can be used to perform the operation S250 described above, which will not be described in detail here.

[0245] The correction module 960 is used to perform residual distance migration correction on the initial image according to the residual distance migration amount corresponding to the initial image, so as to obtain a corrected image corresponding to the initial image. In one embodiment, the correction module 930 can be used to perform the operation S260 described above, which will not be described in detail here.

[0246] According to the residual range migration correction method, device and electronic device of synthetic aperture radar image provided by the present invention, the initial image corresponding to the image to be processed obtained by preprocessing is divided into blocks in azimuth and range directions to obtain multiple initial sub-images and calculate the initial pixel offset data corresponding to the multiple initial sub-images, and the target pixel offset data is generated based on the noise level of the initial pixel offset data corresponding to the multiple initial sub-images to obtain the residual range migration amount corresponding to the initial image, and the residual range migration correction is performed on the SAR initial image according to the residual range migration amount to obtain a high-quality SAR image. Since the residual range migration amount is calculated according to the autocorrelation normalized cross power spectrum, it is not necessary to estimate the residual range migration amount using the sub-block with high signal-to-noise ratio, that is, the large amount of calculation caused by iteration and interpolation operations is avoided, and the imaging quality and robustness of SAR are improved to a certain extent. At the same time, since the computing power of the computer is fully utilized, it can be conveniently deployed on a computing platform such as a field programmable gate array (Field Programmable Gate Array, referred to as FPGA) or a graphics processing unit (Graphics Processing Unit, referred to as GPU). According to an embodiment of the present invention, the computing module 930 includes a computing submodule, a processing submodule and a fitting submodule.

[0247] The calculation submodule is used to calculate the autocorrelation normalized cross-power spectra corresponding to the multiple initial sub-images.

[0248] The processing submodule is used to perform unwrapping processing on the phase of the autocorrelation normalized cross power spectrum to obtain the linear phases of multiple initial sub-images.

[0249] The fitting submodule is used to fit the linear phases of the multiple initial sub-images using the least square method to obtain initial pixel offset data corresponding to the multiple initial sub-images.

[0250] According to an embodiment of the present invention, the generation module 940 includes a first obtaining submodule, a second obtaining submodule, a screening submodule and a splicing submodule.

[0251] The first obtaining submodule is used to perform sliding average processing on the initial pixel offset data corresponding to the multiple initial sub-images according to the initial pixel offset data corresponding to the multiple initial sub-images, so as to obtain sliding average data corresponding to the multiple initial pixel offset data.

[0252] The second obtaining submodule is used to obtain noise data of the initial pixel offset data according to the standard deviation between the initial pixel offset data corresponding to the multiple initial sub-images and the sliding average data.

[0253] The determination submodule is used to screen the initial pixel offset data with the smallest noise data in the same azimuth to obtain the target pixel offset sub-data.

[0254] The splicing submodule is used to splice the target pixel offset sub-data to generate target pixel offset data.

[0255] According to an embodiment of the present invention, the obtaining module 950 includes a superposition submodule and an obtaining submodule.

[0256] The superposition submodule is used to superimpose the target pixel offset sub-data to obtain the target pixel offset data.

[0257] The submodule is used to obtain the residual distance migration amount corresponding to the initial image according to the target pixel offset data.

[0258] According to an embodiment of the present invention, the apparatus 900 further includes a first compensation module and a second compensation module.

[0259] The first compensation module is used to perform azimuth phase error compensation on the corrected image to obtain a compensated image.

[0260] The second compensation module is used to use a phase gradient autofocusing algorithm to perform azimuth phase error compensation on the compensation image to obtain a focused image.

[0261] According to an embodiment of the present invention, any multiple modules of the processing module 910, the partitioning module 920, the calculation module 930, the generation module 940, the acquisition module 950 and the correction module 960 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the processing module 910, the partitioning module 920, the calculation module 930, the generation module 940, the acquisition module 950 and the correction module 960 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or can be implemented in any one of the three implementation methods of software, hardware and firmware or in a suitable combination of any of them. Alternatively, at least one of the processing module 910, the dividing module 920, the calculating module 930, the generating module 940, the obtaining module 950 and the correcting module 960 may be at least partially implemented as a computer program module, which may perform a corresponding function when the computer program module is executed.

[0262] It should be noted that the residual range migration correction device for synthetic aperture radar images in the embodiment of the present invention corresponds to the residual range migration correction method for synthetic aperture radar images in the embodiment of the present invention. The description of the residual range migration correction device for synthetic aperture radar images specifically refers to the residual range migration correction method for synthetic aperture radar images, which will not be repeated here.

[0263] Fig.10 A block diagram of an electronic device suitable for implementing a method for correcting residual range migration of synthetic aperture radar images according to an embodiment of the present invention is shown.

[0264] like Fig.10 As shown, the electronic device 1000 according to an embodiment of the present invention includes a processor 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage part 1008 into a random access memory (RAM) 1003. The processor 1001 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include an onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0265] In RAM 1003, various programs and data required for the operation of electronic device 1000 are stored. Processor 1001, ROM 1002 and RAM 1003 are connected to each other via bus 1004. Processor 1001 performs various operations of the method flow according to the embodiment of the present invention by executing the program in ROM 1002 and / or RAM 1003. It should be noted that the program can also be stored in one or more memories other than ROM 1002 and RAM 1003. Processor 1001 can also perform various operations of the method flow according to the embodiment of the present invention by executing the program stored in one or more memories.

[0266] According to an embodiment of the present invention, the electronic device 1000 may further include an input / output (I / O) interface 1005, which is also connected to the bus 1004. The electronic device 1000 may further include one or more of the following components connected to the I / O interface 1005: an input portion 1006 including a keyboard, a mouse, etc.; an output portion 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 1008 including a hard disk, etc.; and a communication portion 1009 including a network interface card such as a LAN card, a modem, etc. The communication portion 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1010 as needed, so that a computer program read therefrom is installed into the storage portion 1008 as needed.

[0267] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0268] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present invention, the computer-readable storage medium may include the ROM 1002 and / or RAM 1003 described above and / or one or more memories other than ROM 1002 and RAM 1003.

[0269] The embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the synthetic aperture radar image residual range migration correction method provided by the embodiment of the present invention.

[0270] The computer program executes the above functions defined in the system / device of the embodiment of the present invention when it is executed by the processor 1001. According to the embodiment of the present invention, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0271] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 1009, and / or installed from the removable medium 1011. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0272] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1009, and / or installed from the removable medium 1011. When the computer program is executed by the processor 1001, the above functions defined in the system of the embodiment of the present invention are performed. According to the embodiment of the present invention, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0273] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0274] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0275] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in various ways, even if such combinations and / or combinations are not explicitly described in the present invention. In particular, the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in various ways without departing from the spirit and teachings of the present invention. All of these combinations and / or combinations fall within the scope of the present invention.

[0276] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination. The scope of the present invention is defined by the attached claims and their equivalents. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for correcting residual range motion of synthetic aperture radar images, characterized in that: The method comprises: In response to determining that there is a pixel offset in the image to be processed, preprocessing the image to be processed to obtain an initial image corresponding to the image to be processed, wherein the image to be processed includes azimuth data and range data, and the preprocessing includes range pulse compression processing and preliminary geometric correction processing; Dividing the initial image based on the azimuth data and the range data to obtain a plurality of initial sub-images; Calculating autocorrelation normalized cross power spectra corresponding to the plurality of initial sub-images to obtain initial pixel offset data corresponding to the plurality of initial sub-images, including: Calculating autocorrelation normalized cross power spectra corresponding to the plurality of initial sub-images; Performing an unwrapping process on the phase of the autocorrelation normalized cross power spectrum to obtain linear phases of a plurality of the initial sub-images; Using the least square method, fitting the linear phases of the plurality of initial sub-images to obtain initial pixel offset data corresponding to the plurality of initial sub-images; Calculating noise data of initial pixel offset data corresponding to the plurality of initial sub-images, and generating target pixel offset data based on the noise data of the initial pixel offset data corresponding to the plurality of initial sub-images, comprising: According to the initial pixel offset data corresponding to the plurality of initial sub-images, a sliding average process is performed on the initial pixel offset data corresponding to the plurality of initial sub-images to obtain sliding average data corresponding to the plurality of initial pixel offset data; Obtaining noise data of the initial pixel offset data according to a standard deviation between the initial pixel offset data corresponding to the plurality of initial sub-images and the sliding average data; Filter the initial pixel offset data with the smallest noise data in the same azimuth to obtain target pixel offset sub-data; splicing the target pixel offset sub-data to generate the target pixel offset data; According to the target pixel offset data, a residual distance migration amount corresponding to the initial image is obtained, wherein the residual distance migration amount corresponding to the initial image is expressed as follows: in, represents the residual distance migration amount corresponding to the initial image, C represents a constant, represents the target pixel offset data, Indicates the pixel width of the distance upward; According to the residual distance migration amount corresponding to the initial image, residual distance migration correction is performed on the initial image to obtain a corrected image corresponding to the initial image.

2. The method according to claim 1, characterized in that There are overlapping areas between the multiple initial sub-images in azimuth and distance.

3. The method according to claim 1, characterized in that The lengths of the multiple initial sub-images in the distance direction are equal, and the lengths in the azimuth direction are equal.

4. The method according to claim 1, characterized in that The method further comprises: The corrected image is subjected to azimuth phase error compensation to obtain a compensated image.

5. The method according to claim 4, characterized in that The method further comprises: The phase error compensation in azimuth is performed on the compensation image by using a phase gradient self-focusing algorithm to obtain a focused image.

6. A synthetic aperture radar image residual range migration correction device, characterized in that: The device comprises: A processing module, configured to, in response to determining that a pixel offset exists in an image to be processed, pre-process the image to be processed to obtain an initial image corresponding to the image to be processed, wherein the image to be processed includes azimuth data and range data, and the pre-processing includes range pulse compression processing and preliminary geometric correction processing; A division module, used for dividing the initial image based on the azimuth data and the range data to obtain a plurality of initial sub-images; A calculation module, used to calculate the autocorrelation normalized cross power spectra corresponding to the multiple initial sub-images, and obtain the initial pixel offset data corresponding to the multiple initial sub-images, including: calculating the autocorrelation normalized cross power spectra corresponding to the multiple initial sub-images; performing an unwrapping process on the phase of the autocorrelation normalized cross power spectrum to obtain the linear phase of the multiple initial sub-images; using the least square method, fitting the linear phase of the multiple initial sub-images to obtain the initial pixel offset data corresponding to the multiple initial sub-images; A generating module is used to calculate the noise data of the initial pixel offset data corresponding to the plurality of the initial sub-images, and generate the target pixel offset data based on the noise data of the initial pixel offset data corresponding to the plurality of the initial sub-images, including: performing sliding average processing on the initial pixel offset data corresponding to the plurality of the initial sub-images according to the initial pixel offset data corresponding to the plurality of the initial sub-images to obtain sliding average data corresponding to the plurality of the initial pixel offset data; obtaining the noise data of the initial pixel offset data according to the standard deviation between the initial pixel offset data corresponding to the plurality of the initial sub-images and the sliding average data; screening the initial pixel offset data with the smallest noise data in the same azimuth to obtain the target pixel offset sub-data; splicing the target pixel offset sub-data to generate the target pixel offset data; An obtaining module is used to obtain a residual distance migration amount corresponding to the initial image according to the target pixel offset data, wherein the residual distance migration amount corresponding to the initial image is expressed as follows: ,in, represents the residual distance migration amount corresponding to the initial image, C represents a constant, represents the target pixel offset data, Indicates the pixel width of the distance upward; The correction module is used to perform residual distance migration correction on the initial image according to the residual distance migration amount corresponding to the initial image, so as to obtain a corrected image corresponding to the initial image.

7. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors execute the method according to any one of claims 1 to 5.

Images