Background ionospheric correction method suitable for high orbit SAR ground coordinate system imaging

Abstract

The application provides a background ionosphere correction method suitable for high-orbit SAR ground surface coordinate system imaging, which comprises the following steps: receiving a high-orbit SAR echo signal, obtaining corresponding background ionosphere TEC data of the high-orbit SAR echo signal, and performing coarse compensation on the background ionosphere phase error of the echo signal according to the ionosphere TEC data; performing high-orbit SAR ground surface coordinate system imaging on the data after coarse compensation to obtain a large scene image; estimating the phase error of the phase of the echo signal without coarse compensation by using a self-focusing algorithm and the large scene image to obtain an estimation result; fitting the estimation result by using a least square method, determining a coefficient matrix of an ionosphere space-time coupling model corresponding to the large scene image according to the fitting result; dividing the large scene image into a plurality of sub-scene images, performing fine compensation on the background ionosphere phase error of each sub-scene image according to the determined coefficient matrix and each sub-scene image, and completing the correction, so that the correction of the high-orbit SAR ground surface coordinate system imaging is realized.

Description

Technical Field

[0001] This invention relates to the field of radar technology, and specifically to a background ionospheric correction method suitable for high-orbit SAR surface coordinate system imaging. Background Technology

[0002] The ionosphere is an important region of Earth's atmosphere, ranging from 50 km to several thousand km above the ground. High-orbit SAR satellites have an orbital altitude of 36,000 km, far exceeding the altitude of the ionosphere. Compared to low- and medium-orbit SAR satellites, high-orbit SAR signals are significantly affected by ionospheric effects during propagation. Furthermore, due to the long synthetic aperture time and greatly expanded imaging scene of high-orbit SAR, compensation for background ionospheric errors needs to be considered.

[0003] The impact of high-orbit SAR signals propagating entirely through the ionosphere on image quality is significant. Therefore, correcting ionospheric errors is crucial for rapid imaging of high-orbit SAR surface coordinate systems. Existing techniques estimate the ionospheric TEC values ​​of each sub-aperture using molecular aperture and range spectrum, then perform time-fitting along the azimuth direction based on the TEC values ​​of each sub-aperture, and finally infer the ionospheric phase error, which varies along the azimuth direction, into the echo data.

[0004] In high-orbit synthetic aperture radar (SAR) imaging, the fast backpropagation (BP) imaging algorithm based on the surface imaging grid can achieve accurate and efficient imaging for high-orbit SAR. However, since the transmission of high-orbit SAR signals passes through the entire ionosphere, and its synthetic aperture time is very long and the imaging scene is large, the phase error generated by the background ionosphere causes the imaging to defocus. Currently, the ionospheric correction methods for spaceborne SAR are not suitable for correcting the ionospheric phase error in the surface coordinate system imaging of high-orbit SAR. Summary of the Invention

[0005] To address the aforementioned problems in existing technologies, this invention provides a background ionospheric correction method suitable for high-orbit SAR surface coordinate system imaging. Specifically, it includes:

[0006] In a first aspect, the present invention provides a background ionospheric correction method suitable for high-orbit SAR surface coordinate system imaging, comprising:

[0007] Receive high-orbit SAR echo signals;

[0008] Acquire the background ionospheric TEC data corresponding to the high-orbit SAR echo signal, and perform coarse compensation for the background ionospheric phase error of the high-orbit SAR echo signal based on the ionospheric TEC data;

[0009] The data after coarse compensation for background ionospheric phase error was imaged in the high-orbit SAR surface coordinate system to obtain a large-scene image.

[0010] The phase error of the uncompensated phase corresponding to the high-orbit SAR echo signal is estimated by using the self-focusing algorithm and large-scene images, and the estimation result is obtained.

[0011] The estimation results are fitted using the least squares method, and the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image is determined based on the fitted estimation results.

[0012] The large scene image is divided into multiple sub-scene images. Based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image and each sub-scene image, the background ionospheric phase error is precisely compensated for in each sub-scene image to complete the correction of the large scene image.

[0013] Secondly, the present invention also provides a background ionospheric correction device suitable for high-orbit SAR surface coordinate system imaging, comprising:

[0014] The receiving module is used to receive high-orbit SAR echo signals;

[0015] The processing module is used to acquire the background ionospheric TEC data corresponding to the high-orbit SAR echo signal, and to perform coarse compensation for the background ionospheric phase error of the high-orbit SAR echo signal based on the ionospheric TEC data.

[0016] The processing module is also used to perform high-orbit SAR surface coordinate system imaging on the data after coarse compensation for background ionospheric phase error to obtain large scene images;

[0017] The processing module is also used to estimate the phase error of the uncompensated phase corresponding to the high-orbit SAR echo signal through the autofocus algorithm and large scene image, and obtain the estimation result;

[0018] The processing module is also used to fit the estimation results using the least squares method and determine the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image based on the fitted estimation results.

[0019] The processing module is also used to divide the large scene image into multiple sub-scene images, and perform background ionospheric phase error fine compensation on each sub-scene image based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image and each sub-scene image, so as to complete the correction of the large scene image.

[0020] Thirdly, the present invention also provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0021] Memory, used to store computer programs;

[0022] The processor, when executing a program stored in memory, implements any of the methods provided in the first aspect.

[0023] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements any of the methods provided in the first aspect.

[0024] Fifthly, the present invention provides a program product comprising computer program instructions that, when executed, can implement any of the methods provided in the first aspect.

[0025] The beneficial effects of this invention are:

[0026] The present invention provides a background ionospheric correction method for high-orbit SAR surface coordinate system imaging. This method involves receiving high-orbit SAR echo signals; acquiring the corresponding background ionospheric TEC data; coarsely compensating for the background ionospheric phase error of the high-orbit SAR echo signals based on the TEC data; imaging the coarsely compensated background ionospheric phase error data in a high-orbit SAR surface coordinate system to obtain a large-scene image; estimating the uncompensated background ionospheric phase error corresponding to the high-orbit SAR echo signals using a self-focusing algorithm and the large-scene image; and finally fitting the estimation result using the least squares method and applying the fitted estimate. The results determine the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image. The large scene image is divided into multiple sub-scene images. Based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image and each sub-scene image, the background ionospheric phase error is finely compensated for in each sub-scene image to complete the correction of the large scene image. This achieves the correction of the high-orbit SAR surface coordinate system imaging. By combining external measured data to correct the background ionospheric phase error, coarse compensation is achieved. Then, by self-focusing estimation and fitting of molecular scenes to compensate for the remaining phase error, fine compensation is achieved. This reduces the estimation error, improves the compensation effect, and enables the compensated and corrected image to achieve a better aggregation effect.

[0027] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating a background ionospheric correction method for high-orbit SAR surface coordinate system imaging provided by the present invention.

[0029] Figure 2 A simulation diagram provided for this invention;

[0030] Figure 3 Another simulation diagram provided by the present invention;

[0031] Figure 4 This invention provides yet another simulation diagram;

[0032] Figure 5 Another simulation diagram provided by the present invention;

[0033] Figure 6 Another simulation diagram provided by the present invention;

[0034] Figure 7 Another simulation diagram provided by the present invention;

[0035] Figure 8 Another simulation diagram provided by the present invention;

[0036] Figure 9 Another simulation diagram provided by the present invention;

[0037] Figure 10 Another simulation diagram provided by the present invention;

[0038] Figure 11 Another simulation diagram provided by the present invention;

[0039] Figure 12 Another simulation diagram provided by the present invention;

[0040] Figure 13 Another simulation diagram provided by the present invention;

[0041] Figure 14 Another simulation diagram provided by the present invention;

[0042] Figure 15 Another simulation diagram provided by the present invention;

[0043] Figure 16 Another simulation diagram provided by the present invention;

[0044] Figure 17 Another simulation diagram provided by the present invention;

[0045] Figure 18 Another simulation diagram provided by the present invention;

[0046] Figure 19 This is a schematic diagram of the background ionospheric correction device for high-orbit SAR surface coordinate system imaging provided by the present invention. Detailed Implementation

[0047] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0048] Most existing techniques estimate the time-varying data of the ionosphere and compensate it into the echo data. This method does not consider the phase error correction caused by the spatiotemporal coupling of the ionosphere. It has the following drawbacks:

[0049] 1. Only time-varying factors were considered, while space-varying factors were not.

[0050] 2. Compensation is only applied to the echo data of a single target, without considering compensation for the remaining phase error.

[0051] The purpose of this invention is to address the shortcomings of existing technologies by proposing a background ionospheric error correction method suitable for rapid imaging in a high-orbit SAR surface coordinate system. First, high-orbit SAR echo signals are received. Second, coarse compensation is achieved by compensating for background ionospheric phase errors based on externally measured real-time ionospheric TEC data. Third, rapid imaging in the high-orbit SAR surface coordinate system is performed, and the remaining phase error is estimated using self-focusing. Least-squares fitting is combined to reduce the estimation error, and considering the spatiotemporal coupling error of the ionosphere, the spatiotemporal coupling model coefficients of the ionosphere within the large scene are calculated. Finally, the large scene is divided into multiple smaller scene images, and the ionospheric phase errors of the smaller scene images are compensated separately in the pseudo-echo domain using the solved coupling coefficients, achieving fine compensation. This invention fully considers the impact of spatiotemporal coupling changes of the ionosphere on imaging in large-scale high-orbit SAR. It achieves coarse compensation by correcting background ionospheric phase errors using measured real-time ionospheric TEC data, then performs self-focusing to estimate the remaining phase error, and combines least-squares fitting to reduce the estimation error and compensate for the remaining phase error of the ionosphere to achieve fine compensation. This invention can quickly and accurately compensate for phase errors caused by the ionosphere, thus solving the problem of background ionospheric error correction in high-orbit SAR surface coordinate system imaging.

[0052] Figure 1 This is a flowchart illustrating a background ionospheric correction method for high-orbit SAR surface coordinate system imaging provided by the present invention, as shown below. Figure 1 As shown, the method includes:

[0053] S101, Receive high-orbit SAR echo signals.

[0054] In one possible implementation, the expression for the high-orbit SAR echo signal is:

[0055]

[0056] Among them, s(f r ,t a ) represents the high-orbit SAR echo signal. This indicates the position of the high-orbit SAR signal at time ta in the azimuth direction. The TEC value at the point of puncture, where c represents the speed of light, f rf0 represents the center frequency of the signal, where f0 represents the distance-directed frequency. Represents the target in the scene The signal slant range history at point j, where j represents a complex number.

[0057] S102. Obtain the background ionospheric TEC data corresponding to the high-orbit SAR echo signal, and perform coarse compensation for the background ionospheric phase error of the high-orbit SAR echo signal based on the ionospheric TEC data.

[0058] In one possible implementation, ionospheric TEC data corresponding to the high-orbit SAR echo signal is acquired, and coarse compensation is performed on the background ionospheric phase error of the high-orbit SAR echo signal based on the ionospheric TEC data, including the following steps A1-A3:

[0059] A1. Obtain the radar location information and target location information corresponding to the high-orbit SAR echo signal, and determine the location of the penetration point of the high-orbit SAR echo signal through the background ionosphere based on the obtained location information.

[0060] A2. Obtain ionospheric TEC data during the imaging time and query the TEC value at the puncture point corresponding to each pulse of the high-orbit SAR echo signal.

[0061] A3. Based on the TEC value at the puncture point corresponding to each pulse, correct the background ionospheric phase error of the corresponding pulse.

[0062] For example, background ionospheric TEC data during the imaging time period is downloaded from the IGS website, and the TEC value at the background ionospheric puncture point location is queried for each pulse time of the high-orbit SAR echo signal. The background ionospheric phase error is corrected for each pulse to achieve coarse compensation.

[0063] S103. After coarsely compensating for the background ionospheric phase error, perform high-orbit SAR surface coordinate system imaging on the data to obtain a large-scene image.

[0064] S104. Using the autofocus algorithm and large-scene images, estimate the phase error of the uncompensated phase corresponding to the high-orbit SAR echo signal to obtain the estimation result.

[0065] S105. Fit the estimation results using the least squares method, and determine the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image based on the fitted estimation results.

[0066] S106. Divide the large scene image into multiple sub-scene images. Based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image and each sub-scene image, perform fine compensation for the background ionospheric phase error of each sub-scene image to complete the correction of the large scene image.

[0067] In one possible implementation, a large scene image is divided into multiple sub-scene images, including: dividing the large scene image into multiple sub-distance blocks along the distance direction; and for any sub-distance block, dividing it into multiple sub-directional blocks along the azimuth direction.

[0068] For example, the image is first divided into sub-distance blocks along the distance direction, and then the sub-distance blocks are divided into sub-azimuth blocks along the azimuth direction, thereby dividing the image with a scene size of 500km*500km into multiple sub-scene images of 50km*50km.

[0069] This invention divides a large scene image into multiple sub-scene images and then performs further correction, which can fully take into account the spatiotemporal coupling error of the ionosphere and improve the compensation accuracy and effect.

[0070] In one possible implementation, for any first sub-scene image among multiple sub-scene images, fine compensation for background ionospheric phase error is performed on the first sub-scene image based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image and the first sub-scene image. This includes: determining the pseudo-echo corresponding to the first sub-scene image through Fourier transform and inverse Fourier transform; determining the ionospheric phase error of the first sub-scene image region based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image, and compensating the ionospheric phase error of the first sub-scene image region into the pseudo-echo corresponding to the first sub-scene image to obtain the compensation result; processing the compensation result based on Fourier transform and inverse Fourier transform to determine the focused sub-scene image corresponding to the first sub-scene image after ionospheric error compensation; and determining the fine compensation result of the large scene image based on the focused sub-scene images corresponding to each sub-scene image.

[0071] Specifically, the pseudo-echo corresponding to the first sub-scene image is determined through Fourier transform and inverse Fourier transform, including the following steps B1 and B2:

[0072] B1. After padding the first sub-scene image with zeros at both ends, perform a Fourier transform in the orientation direction to obtain the first transform result.

[0073] B1. After multiplying the first transformation result by a first preset value in the azimuth frequency domain, perform an inverse Fourier transform in the azimuth direction to obtain the pseudo echo corresponding to the first sub-scene image.

[0074] The expression for the first preset value is:

[0075]

[0076] Among them, f a Indicates azimuth frequency, K a (r) indicates the azimuth tuning frequency in the current range direction.

[0077] Specifically, the compensation results are processed based on Fourier transform and inverse Fourier transform to determine the focused sub-scene image after compensating for ionospheric error, corresponding to the first sub-scene image, including C1 and C2:

[0078] C1. Perform a Fourier transform on the compensation result in the azimuth direction to obtain the second transform result.

[0079] C2. After multiplying the second transformation result by the second preset value in the azimuth frequency domain, perform an inverse Fourier transform in the azimuth direction to obtain the focused sub-scene image corresponding to the first sub-scene image after compensating for ionospheric error.

[0080] The expression for the second preset value is:

[0081]

[0082] Among them, f a Indicates azimuth frequency, K a (r) indicates the azimuth tuning frequency in the current range direction.

[0083] For example, zero-padding is used to obtain sub-scene image I1 for any sub-scene image. The sub-scene image I1 data is then subjected to a Fourier transform in the azimuth direction, and multiplied in the azimuth frequency domain by... Then, an inverse Fourier transform in the azimuth direction is performed to obtain the pseudo-echo I2; the ionospheric phase error of the sub-scene image region is obtained based on the calculated spatiotemporal coupling model coefficient matrix. The phase error is compensated into I2 to obtain I3; an azimuth Fourier transform is performed on I3, and the result is multiplied by in the azimuth frequency domain. Then, an inverse Fourier transform in the azimuth direction is performed to obtain the focused sub-scene image I4 after compensating for ionospheric errors. The same method is used to traverse each sub-scene to compensate for the remaining phase error of the ionosphere and obtain the entire focused image I, thus achieving fine compensation.

[0084] This invention combines external measured data to correct the background ionospheric phase error to achieve coarse compensation, and then compensates for the remaining phase error by self-focusing estimation and fitting molecular scene to achieve fine compensation. This reduces estimation error, improves compensation effect, and enables the compensated and corrected image to achieve better focusing effect.

[0085] This invention provides a background ionospheric correction method for high-orbit SAR surface coordinate system imaging. The method involves receiving high-orbit SAR echo signals; acquiring the corresponding background ionospheric TEC data; coarsely compensating for the background ionospheric phase error of the high-orbit SAR echo signals based on the TEC data; imaging the coarsely compensated background ionospheric phase error data in a high-orbit SAR surface coordinate system to obtain a large-scene image; estimating the uncompensated background ionospheric phase error corresponding to the high-orbit SAR echo signals using an autofocus algorithm and the large-scene image; fitting the estimation result using the least squares method; determining the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large-scene image based on the fitted estimation result; dividing the large-scene image into multiple sub-scene images; and finely compensating for the background ionospheric phase error of each sub-scene image based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large-scene image and each sub-scene image to complete the correction of the large-scene image. This achieves the correction of high-orbit SAR surface coordinate system imaging, and the corrected image can achieve target focusing effect.

[0086] To further demonstrate the beneficial effects of the present invention, a set of simulation experimental data is also provided, as follows:

[0087] The simulation parameters are shown in Table 1:

[0088] Table 1 Simulation Parameters

[0089]

[0090]

[0091] Background ionospheric TEC data is provided by the IGS website. The specific TEC value can be obtained by looking up a table after calculating the location of the puncture point in the background ionospheric traversed by the radar to reach the target and the imaging time.

[0092] Figure 2 This is a schematic diagram showing the distribution of point targets. Figure 3 This diagram illustrates the echo signals after incorporating ionospheric errors. Nine point targets were simulated and generated based on an ionospheric model. The horizontal axis of the point target distribution map represents longitude, and the vertical axis represents latitude.

[0093] Figures 4-6 These are measured TEC data distribution maps showing the path of radar to targets at the lower left edge, center, and upper right edge of the scene. The horizontal axis represents azimuth time in seconds, and the vertical axis represents the ionospheric TEC value traversed in TECUs. Specifically... Figure 4 Distribution of time-varying TEC data corresponding to the target's azimuth at the lower edge point; Figure 5 Distribution of time TEC data corresponding to the azimuth of the target at the center point; Figure 6 The distribution of time TEC data corresponding to the target azimuth at the upper right edge point.

[0094] Figures 7-12 Fast backpropagation (BP) based on a surface imaging grid was performed on the echoes generated by adding background ionospheric errors to nine point targets within the scene. The resulting images show the lower left edge point target, the center point target, and the upper right edge point target. It can be observed that the background ionospheric phase error causes defocusing. Specifically, Figure 7 Corresponding to the bottom left edge point target contour map; Figure 8 Corresponding center point target Contour diagram; Figure 9 Corresponding to the top right edge point target contour map; Figure 10 The target's orientation is aligned with the PSLR at the lower left edge point. Figure 11 PSLR corresponding to the center point target azimuth; Figure 12 The target azimuth direction corresponding to the upper right edge point is PSLR.

[0095] Figures 13-18 The image shows the results obtained after correcting the received high-orbit SAR echo signal using the background ionospheric correction method for high-orbit SAR surface coordinate system imaging proposed in this paper. The results after compensating the lower left edge point target, center point target, and upper right edge point target are as follows. Figure 5 As shown. Specifically, Figure 13 Corresponding to the contour map of the target point at the lower left edge after self-focusing correction proposed in this paper;

[0096] Figure 14 Corresponding to the center point target contour map proposed in this paper after self-focusing correction; Figure 15 Corresponding to the contour map of the target point at the upper right edge after self-focusing correction proposed in this paper; Figure 16 This corresponds to the target azimuth PSLR of the lower left edge point after self-focusing correction proposed in this paper; Figure 17 This corresponds to the self-focusing correction center point target azimuth PSLR proposed in this paper; Figure 18 This corresponds to the target azimuth PSLR of the upper right edge point after self-focusing correction proposed in this paper.

[0097] It can be observed that by performing coarse compensation based on measured background ionospheric TEC data before imaging, and then performing fine compensation of the molecular scene through self-focusing estimation and solving the background ionospheric phase error model coefficients, the target focusing effect is good, which is suitable for background ionospheric correction in high-orbit SAR surface coordinate system imaging.

[0098] Figure 19 This is a schematic diagram of the background ionospheric correction device for high-orbit SAR surface coordinate system imaging provided by the present invention, as shown below. Figure 19 As shown, the device includes:

[0099] Receiver module 191 is used to receive high-orbit SAR echo signals.

[0100] The processing module 192 is used to acquire the background ionospheric TEC data corresponding to the high-orbit SAR echo signal, and to perform coarse compensation for the background ionospheric phase error of the high-orbit SAR echo signal based on the ionospheric TEC data.

[0101] The processing module 192 is also used to perform high-orbit SAR surface coordinate system imaging on the data after coarse compensation for background ionospheric phase error to obtain large scene images.

[0102] The processing module 192 is also used to estimate the phase error of the uncompensated background ionosphere corresponding to the high-orbit SAR echo signal by using a self-focusing algorithm and a large scene image, and obtain the estimation result.

[0103] The processing module 192 is also used to fit the estimation results using the least squares method and determine the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image based on the fitted estimation results.

[0104] The processing module 192 is also used to divide the large scene image into multiple sub-scene images, and perform background ionospheric phase error fine compensation on each sub-scene image according to the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image and each sub-scene image, so as to complete the correction of the large scene image.

[0105] This invention also provides an electronic device structure, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, communication interface, and memory communicate with each other via the communication bus.

[0106] Memory, used to store computer programs;

[0107] When a processor executes a program stored in memory, it implements the steps provided in the above method embodiments.

[0108] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0109] The method provided in this invention can be applied to electronic devices. Specifically, the electronic device can be a desktop computer, a portable computer, a smart mobile terminal, a server, etc. No limitation is made herein; any electronic device that can implement this invention falls within the protection scope of this invention.

[0110] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps provided in the above-described method embodiments.

[0111] For the embodiments of the device / electronic device / storage medium, since they are basically similar to the method embodiments, the description is relatively simple. For specific details and beneficial effects, please refer to the description of the method embodiments.

[0112] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0113] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for background ionospheric correction suitable for high-orbit SAR surface coordinate system imaging, characterized in that, include: Receive high-orbit SAR echo signals; Obtain the background ionospheric TEC data corresponding to the high-orbit SAR echo signal, and perform coarse compensation for the background ionospheric phase error of the high-orbit SAR echo signal based on the ionospheric TEC data; The data after coarse compensation for background ionospheric phase error was imaged in the high-orbit SAR surface coordinate system to obtain a large-scene image. The phase error of the uncompensated phase corresponding to the high-orbit SAR echo signal is estimated using the autofocus algorithm and the large scene image, and the estimation result is obtained. The estimation results are fitted using the least squares method, and the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image is determined based on the fitted estimation results. The large scene image is divided into multiple sub-scene images. Based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image and each sub-scene image, the background ionospheric phase error is precisely compensated for in each sub-scene image to complete the correction of the large scene image.

2. The method according to claim 1, characterized in that, For any first sub-scene image among the plurality of sub-scene images, based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image and the first sub-scene image, fine compensation for background ionospheric phase error is performed on the first sub-scene image, including: The pseudo-echo corresponding to the first sub-scene image is determined by Fourier transform and inverse Fourier transform. The ionospheric phase error of the first sub-scene image region is determined based on the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image, and the ionospheric phase error of the first sub-scene image region is compensated into the pseudo echo corresponding to the first sub-scene image to obtain the compensation result. The compensation results are processed based on Fourier transform and inverse Fourier transform to determine the focused sub-scene image after compensating for ionospheric error corresponding to the first sub-scene image. The fine compensation result of the large scene image is determined based on the focused sub-scene image corresponding to each of the sub-scene images.

3. The method according to claim 2, characterized in that, The step of determining the pseudo-echo corresponding to the first sub-scene image through Fourier transform and inverse Fourier transform includes: After padding the first sub-scene image with zeros at both ends, perform a Fourier transform in the orientation direction to obtain the first transform result; After multiplying the first transformation result by a first preset value in the azimuth frequency domain, an inverse Fourier transform in the azimuth direction is performed to obtain the pseudo echo corresponding to the first sub-scene image. The expression for the first preset value is: Among them, f a Indicates azimuth frequency, K a (r) indicates the azimuth tuning frequency in the current range direction.

4. The method according to claim 2 or 3, characterized in that, The process of processing the compensation result based on Fourier transform and inverse Fourier transform to determine the focused sub-scene image corresponding to the first sub-scene image after compensating for ionospheric error includes: Perform a Fourier transform on the compensation result in the azimuth direction to obtain a second transform result; After multiplying the second transformation result by a second preset value in the azimuth frequency domain, an inverse Fourier transform in the azimuth direction is performed to obtain the focused sub-scene image corresponding to the first sub-scene image after compensating for ionospheric error. The expression for the second preset value is: Among them, f a Indicates azimuth frequency, K a (r) indicates the azimuth tuning frequency in the current range direction.

5. The method according to claim 1 or 2, characterized in that, The step of dividing the large scene image into multiple sub-scene images includes: The large scene image is divided into multiple sub-distance blocks along the distance direction; For any given sub-distance block, divide it into multiple sub-direction blocks along the azimuth direction.

6. The method according to claim 1 or 2, characterized in that, The expression for the high-orbit SAR echo signal is: in, Indicates the azimuth direction at slower time t a High-orbit SAR signal to target position at any time The TEC value at the point of puncture, where c represents the speed of light, f r f0 represents the center frequency of the signal, where f0 represents the distance-directed frequency. Represents the target in the scene The signal slant range history at point j, where j represents a complex number.

7. The method according to claim 1 or 2, characterized in that, The step of acquiring the ionospheric TEC data corresponding to the high-orbit SAR echo signal and performing coarse compensation for the background ionospheric phase error of the high-orbit SAR echo signal based on the ionospheric TEC data includes: The location information of the radar corresponding to the high-orbit SAR echo signal and the location information of the target corresponding to the high-orbit SAR echo signal are obtained, and the location of the penetration point of the high-orbit SAR echo signal through the background ionosphere is determined based on the obtained location information. Acquire ionospheric TEC data during the imaging time and query the TEC value at the puncture point corresponding to each pulse of the high-orbit SAR echo signal; The background ionospheric phase error of each pulse is corrected based on the TEC value at the puncture point corresponding to each pulse.

8. A background ionospheric correction device suitable for high-orbit SAR surface coordinate system imaging, characterized in that, include: The receiving module is used to receive high-orbit SAR echo signals; The processing module is used to acquire the background ionospheric TEC data corresponding to the high-orbit SAR echo signal, and to perform coarse compensation for the background ionospheric phase error of the high-orbit SAR echo signal based on the ionospheric TEC data. The processing module is also used to perform high-orbit SAR surface coordinate system imaging on the data after coarse compensation for background ionospheric phase error to obtain large scene images; The processing module is also used to estimate the phase error of the uncompensated phase corresponding to the high-orbit SAR echo signal by using the autofocus algorithm and the large scene image, and obtain the estimation result; The processing module is further configured to fit the estimation result using the least squares method, and determine the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image based on the fitted estimation result; The processing module is further configured to divide the large scene image into multiple sub-scene images, and perform background ionospheric phase error fine compensation on each sub-scene image according to the coefficient matrix of the ionospheric spatiotemporal coupling model corresponding to the large scene image and each sub-scene image, so as to complete the correction of the large scene image.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

Images