Satellite-borne synthetic aperture radar in-orbit radiation correction method and device

Abstract

The invention provides a satellite-borne synthetic aperture radar in-orbit radiation correction method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining echo data of a synthetic aperture radar, and obtaining a first antenna pattern; preprocessing the echo data to obtain preprocessed echo data; performing compression processing on the first antenna pattern to obtain a two-dimensional lookup table; constructing a comprehensive compensation factor according to the two-dimensional lookup table; introducing the comprehensive compensation factor into a pre-constructed first imaging model to obtain a second imaging model; and inputting the preprocessed echo data into the second imaging model to obtain target echo data. According to the invention, the echo data of the synthetic aperture thunder is corrected before imaging, the processing flow is simplified, the consumption of computing resources is reduced, the time consumption is shortened while the precision is improved, and the imaging efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of synthetic aperture radar reconnaissance signal processing technology, and more specifically, to an on-orbit radiation correction method, device, electronic equipment, and storage medium for spaceborne synthetic aperture radar. Background Technology

[0002] Traditional radiometric correction methods are typically performed independently after imaging, involving multiple correction steps such as system calibration, antenna pattern correction, scan gain compensation, and field calibration. While this method can improve image radiometric accuracy to some extent, its complex processing flow, high computational load, and high storage requirements make it difficult to achieve real-time or near-real-time processing under conditions of limited onboard resources. Especially in scenarios such as disaster emergency response, it cannot meet the timeliness requirements for rapidly acquiring high-precision images.

[0003] Furthermore, due to the strict limitations in power consumption, computing resources, and storage capacity faced by spaceborne platforms, traditional ground-based processing methods require downloading raw data to ground stations for processing before uploading it back to users. This entire process is time-consuming and severely restricts the application efficiency of Synthetic Aperture Radar (SAR) data. Although some studies have attempted to implement partial imaging processing on-board, the processing mode of separating radiometric correction and imaging has not fundamentally resolved the contradiction between resources and real-time performance.

[0004] Application content The purpose of this application is to provide an on-orbit radiation correction method, device, electronic equipment, and storage medium for spaceborne synthetic aperture radar, which corrects the echo data of synthetic aperture radar before imaging, simplifies the processing flow, reduces the consumption of computing resources, and improves accuracy while shortening the time consumption and improving imaging efficiency.

[0005] In a first aspect, embodiments of this application provide an on-orbit radiation correction method for a spaceborne synthetic aperture radar, the method comprising: Acquire echo data from synthetic aperture radar and obtain the first antenna pattern; The echo data is preprocessed to obtain preprocessed echo data; The first antenna pattern is compressed to obtain a two-dimensional lookup table; Construct a comprehensive compensation factor based on the two-dimensional lookup table; The comprehensive compensation factor is introduced into the pre-constructed first imaging model to obtain the second imaging model; The preprocessed echo data is input into the second imaging model to obtain the target echo data.

[0006] In the above implementation process, the antenna pattern is compressed to reduce its storage space, and a comprehensive compensation factor is constructed. The echo data of the synthetic aperture radar is corrected before imaging, simplifying the processing flow, reducing the consumption of computing resources, improving accuracy while shortening the time consumption, and improving imaging efficiency.

[0007] Further, the step of preprocessing the echo data to obtain preprocessed echo data includes: The echo data is de-DC operated according to the sliding window mean algorithm to obtain the echo data after de-DC operation; Construct the scan gain factor; The echo data after DC removal operation is scanned and corrected according to the scan gain factor to obtain the scan gain corrected echo data. The echo data after scanning gain correction is determined to be the preprocessed echo data.

[0008] In the above implementation process, by performing DC removal on the echo data and constructing a scanning gain factor to correct its scanning gain, the echo data can be preprocessed before imaging, improving the accuracy of the echo data and providing data support for the subsequent imaging process.

[0009] Furthermore, the formula for constructing the scanning gain factor is as follows: ; in, Maximum gain at the beam center It is the off-axis angle. The attenuation coefficient is... The scan gain factor is mentioned above.

[0010] In the above implementation process, the scanning gain factor is calculated based on the maximum gain at the beam center, the off-axis angle, and the attenuation coefficient. This compensates for the gain attenuation caused by the change in the depression angle in the range direction, significantly reduces the dynamic range pressure of subsequent processing, and avoids the risk of numerical overflow in post-processing compensation.

[0011] Furthermore, the formula for performing DC removal operation on the echo data according to the sliding window averaging algorithm to obtain the DC-removed echo data is as follows: ; Where N is the number of samples within the sliding window, and S is the echo data. The echo data after the DC removal operation is given, where t is the azimuth time and i is the index of the sample within the sliding window. For distance to time, For the first in the sliding window The time corresponding to each sample.

[0012] In the above implementation process, performing DC removal on the echo data can effectively eliminate the DC bias of the system and improve the dynamic range of signal processing.

[0013] Further, the step of compressing the first antenna pattern to obtain a two-dimensional lookup table includes: By capturing key parameters of the first antenna pattern, the second antenna pattern is obtained; The second antenna pattern is subjected to mesh sparsification to obtain the two-dimensional lookup table.

[0014] In the above implementation process, capturing key parameters of the first antenna pattern can effectively extract the physical characteristics in the first antenna pattern. Then, the extracted physical characteristics can be compressed to reduce the storage space of the antenna pattern, thus providing support for improving the real-time performance of the correction.

[0015] Furthermore, by capturing key parameters of the first antenna pattern, the formula for obtaining the second antenna pattern is: ; in, It is the azimuth angle. The pitch angle, Antenna length For wavelength, The peak value corresponding to the first antenna pattern. Let sinc() be the second antenna pattern.

[0016] In the above implementation process, by capturing key parameters based on the peak value of the first antenna pattern and multiple geometric parameters, the physical and mathematical characteristics of the antenna pattern can be captured, the key features of the antenna pattern can be extracted, and data redundancy can be reduced.

[0017] Further, the step of constructing the comprehensive compensation factor based on the two-dimensional lookup table includes: Construct the antenna pattern compensation factor based on the two-dimensional lookup table; Construct system gain, processing chain gain, and external calibration parameters; Obtain the third factor in the range-Doppler domain of the first imaging model; The third factor is adjusted based on the antenna pattern compensation factor, the system gain, the processing chain gain, and the external calibration parameters to obtain the comprehensive compensation factor.

[0018] In the above implementation process, the third factor is adjusted according to the antenna pattern compensation factor, system gain, processing chain gain and external calibration parameters to obtain the comprehensive compensation factor, which can adjust the system gain, ensure the accuracy of radiation correction, and further improve the radiation uniformity and realism of the imaging.

[0019] Further, the step of constructing the antenna pattern compensation factor based on the two-dimensional lookup table includes: Obtain real-time geometric parameters; The real-time geometric parameters are used as an index to look up the input parameters corresponding to the real-time geometric parameters in the two-dimensional lookup table; The antenna pattern compensation factor is obtained based on the input parameters.

[0020] In the above implementation process, the input parameters corresponding to the two-dimensional lookup table are found according to the real-time geometric parameters to further obtain the antenna pattern compensation factor, ensuring the accuracy of the antenna pattern compensation factor and simplifying the calculation process.

[0021] Secondly, embodiments of this application also provide an on-orbit radiation correction device for a spaceborne synthetic aperture radar, the device comprising: The acquisition module is used to acquire echo data from the synthetic aperture radar and to acquire the first antenna pattern. The preprocessing module is used to preprocess the echo data to obtain preprocessed echo data; A compression module is used to compress the radiation pattern of the first antenna to obtain a two-dimensional lookup table; The construction module is used to construct a comprehensive compensation factor based on the two-dimensional lookup table; An introduction module is used to introduce the comprehensive compensation factor into a pre-constructed first imaging model to obtain a second imaging model; An imaging module is used to input the preprocessed echo data into the second imaging model to obtain target echo data.

[0022] In the above implementation process, the antenna pattern is compressed to reduce its storage space, and a comprehensive compensation factor is constructed. The echo data of the synthetic aperture radar is corrected before imaging, simplifying the processing flow, reducing the consumption of computing resources, improving accuracy while shortening the time consumption, and improving imaging efficiency.

[0023] Thirdly, an electronic device provided in this application includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method as described in any of the first aspects.

[0024] Fourthly, embodiments of this application provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described in any of the first aspects.

[0025] Other features and advantages of this disclosure will be set forth in the following description, or some features and advantages may be inferred from the description or determined without doubt, or may be learned by practicing the techniques described above.

[0026] It can be implemented in accordance with the contents of the specification. The preferred embodiments of this application are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0027] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation on the range. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 A flowchart illustrating the on-orbit radiation correction method for a spaceborne synthetic aperture radar is provided for embodiments of this application. Figure 2 A schematic diagram of the structural composition of an on-orbit radiation correction device for a spaceborne synthetic aperture radar is provided for embodiments of this application; Figure 3 This is a schematic diagram of the structural composition of the electronic device provided in the embodiments of this application. Detailed Implementation

[0029] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0030] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0031] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but are not intended to limit the scope of this application.

[0032] Traditional radiometric correction methods are typically performed independently after imaging. While this approach can improve image radiometric accuracy to some extent, its processing is complex, computationally intensive, and requires significant storage, making it difficult to achieve real-time or near-real-time processing under resource-constrained onboard conditions. This is especially problematic in disaster emergency response scenarios, where the demands on the onboard platform, computational resources, and storage resources are excessive, failing to meet the timeliness requirements for rapidly acquiring high-precision images.

[0033] This application abandons the serial processing mode of imaging first and then correction, and deeply integrates the radiometric correction with the imaging process, realizing synchronous processing of imaging and correction. It can perform radiometric correction in real time under the limited resources of the spaceborne platform, thus meeting the real-time requirements.

[0034] Example 1 Figure 1 This is a flowchart illustrating the on-orbit radiation correction method for spaceborne synthetic aperture radar provided in this application embodiment, as shown below. Figure 1 As shown, the method includes: S1, acquire the echo data of the synthetic aperture radar and acquire the first antenna pattern; S2, preprocess the echo data to obtain preprocessed echo data; S3, Compress the radiation pattern of the first antenna to obtain a two-dimensional lookup table; S4, Construct a comprehensive compensation factor based on a two-dimensional lookup table; S5, the comprehensive compensation factor is introduced into the pre-constructed first imaging model to obtain the second imaging model; S6. Input the preprocessed echo data into the second imaging model to obtain the target echo data.

[0035] In the above implementation process, the antenna pattern is compressed to reduce its storage space, and a comprehensive compensation factor is constructed. The echo data of the synthetic aperture radar is corrected before imaging, simplifying the processing flow, reducing the consumption of computing resources, improving accuracy while shortening the time consumption, and improving imaging efficiency.

[0036] This application avoids data redundancy and processing delays inherent in traditional methods, significantly improving processing efficiency. This is particularly important in scenarios such as emergency response where real-time acquisition of high-precision imagery is required.

[0037] Furthermore, S2 includes: The echo data is de-DCed using the sliding window mean algorithm to obtain the echo data after de-DCing. Construct the scan gain factor; The echo data after DC removal operation is corrected by scanning gain factor to obtain the echo data after scanning gain correction. The echo data after scanning gain correction is determined to be the preprocessed echo data.

[0038] In the above implementation process, by performing DC removal on the echo data and constructing a scanning gain factor to correct its scanning gain, the echo data can be preprocessed before imaging, improving the accuracy of the echo data and providing data support for the subsequent imaging process.

[0039] This application proactively moves the scanning gain correction to the signal preprocessing stage, performing real-time compensation in the original echo domain. This shifts the elimination of radiation errors from the image domain to the signal domain, thereby suppressing the problem at its source.

[0040] DC de-biasing can eliminate DC bias.

[0041] Furthermore, the formula for constructing the scanning gain factor is as follows: ; in, Maximum gain at the beam center It is the off-axis angle. The attenuation coefficient is... This is the scan gain factor.

[0042] In the above implementation process, the scanning gain factor is calculated based on the maximum gain at the beam center, the off-axis angle, and the attenuation coefficient. This compensates for the gain attenuation caused by the change in the depression angle in the range direction, significantly reduces the dynamic range pressure of subsequent processing, and avoids the risk of numerical overflow in post-processing compensation.

[0043] The scanning gain factor is constructed based on the system calibration constant and distance attenuation model. It can calculate and apply scanning gain correction in real time and perform gain pre-compensation directly in the original echo signal domain.

[0044] It effectively purifies the signal and significantly compresses the dynamic range faced by subsequent imaging processing, reduces the requirements for processor numerical accuracy and bit width, avoids the risk of overflow in the calculation process, and reduces the burden on the imaging algorithm chain as a whole, thus ensuring the stability and reliability of the back-end integrated processing.

[0045] Furthermore, the echo data is deDC-processed using the sliding window averaging algorithm, and the formula for obtaining the deDC-processed echo data is as follows: ; Where N is the number of samples within the sliding window, and S is the echo data. This represents the echo data after DC removal, where t is the azimuth time and i is the index of the sample within the sliding window. For distance to time, For the first in the sliding window The time corresponding to each sample.

[0046] In the above implementation process, performing DC removal on the echo data can effectively eliminate the DC bias of the system and improve the dynamic range of signal processing.

[0047] The sliding window operates independently on each distance gate, which can effectively eliminate DC bias and improve the dynamic range of signal processing.

[0048] For example, let's take the j-th distance gate as an example. Assume there are a total of M azimuth sampling points (i.e., M values ​​in slow time t), the j-th distance gate (i.e., τ=τj), and the length of the sliding window is N (N can be 64, 128, etc.).

[0049] Extracting all data from the j-th range gate from the complete echo data will yield a one-dimensional sequence of length M: ; This sequence represents the signal changes received by the radar platform at a fixed distance as it flies over the target area.

[0050] Place the sliding window in the sequence The starting position is such that the window covers the first N directional sampling points, i.e., from t1 to tN.

[0051] Calculate the mean (DC component) within the window: Calculate the average of N data points within the current window: ; Move the window backward by one azimuth sampling point (i.e., a step size of 1), and repeat the above steps until the sliding window has traversed the entire azimuth sequence. .

[0052] Furthermore, S3 includes: By capturing key parameters of the first antenna pattern, the second antenna pattern can be obtained; The second antenna pattern is subjected to grid sparsification to obtain a two-dimensional lookup table.

[0053] In the above implementation process, capturing key parameters of the first antenna pattern can effectively extract the physical characteristics in the first antenna pattern. Then, the extracted physical characteristics can be compressed to reduce the storage space of the antenna pattern, thus providing support for improving the real-time performance of the correction.

[0054] This application defines sparsity criteria including the curvature / gradient criterion: in regions where the orientation pattern changes gently, the importance of data points is low, and sparsification is permissible. In regions where the curvature / gradient changes drastically, more data points need to be retained.

[0055] After applying the sparsity algorithm, a set of selected, non-uniformly distributed azimuth and elevation grid points is obtained, along with the second-day azimuth pattern corresponding to the data points.

[0056] This application realizes a paradigm shift from storing massive amounts of data to storing simplified models. Instead of directly storing the gain value of each sampling point, it captures the mathematical essence and physical characteristics of the antenna pattern through parametric modeling. Combined with grid sparsification technology, it stores only the key parameters and sparse grid points that can reproduce the entire pattern with high precision. High-resolution three-dimensional pattern data (i.e., the second antenna pattern) is obtained through ground antenna pattern measurement experiments.

[0057] This application uses the original antenna pattern as the first antenna pattern and the first antenna pattern captured after parametric modeling as the second antenna pattern.

[0058] By employing parametric modeling and mesh sparsification methods, the radiation pattern of the first antenna is compressed into a lightweight two-dimensional lookup table (LUT), which greatly saves on-board storage resources.

[0059] Furthermore, by capturing key parameters of the first antenna pattern, the formula for the second antenna pattern is obtained: ; in, It is the azimuth angle. The pitch angle, Antenna length For wavelength, The peak value corresponding to the first antenna pattern. This is the second antenna direction chart, and sinc() is the Singer function.

[0060] In the above implementation process, by capturing key parameters based on the peak value of the first antenna pattern and multiple geometric parameters, the physical and mathematical characteristics of the antenna pattern can be captured, the key features of the antenna pattern can be extracted, and data redundancy can be reduced.

[0061] Furthermore, the steps for constructing the comprehensive compensation factor based on the two-dimensional lookup table include: Construct the antenna pattern compensation factor based on a two-dimensional lookup table; Construct system gain, processing chain gain, and external calibration parameters; Obtain the third factor in the range-Doppler domain of the first imaging model; The third factor is adjusted based on the antenna pattern compensation factor, system gain, processing chain gain, and external calibration parameters to obtain the comprehensive compensation factor.

[0062] In the above implementation process, the third factor is adjusted according to the antenna pattern compensation factor, system gain, processing chain gain and external calibration parameters to obtain the comprehensive compensation factor, which can adjust the system gain, ensure the accuracy of radiation correction, and further improve the radiation uniformity and realism of the imaging.

[0063] In this application, the initial first imaging model (the first imaging model in this application adopts the CS imaging algorithm) includes a first factor, a third factor in the range Doppler domain, and a second factor in the two-dimensional frequency domain. The first factor and the second factor are not changed, and this application only adjusts the third factor.

[0064] By combining the integrated antenna pattern compensation factor in the range-Doppler domain, system gain, processing chain gain, and external calibration parameters, a comprehensive compensation factor is formed. This comprehensive compensation factor is no longer a pure phase factor, but a combined amplitude and phase compensation factor signal, ultimately achieving radiation calibration and energy normalization.

[0065] System gain is the combined gain of all hardware components in the SAR transmit and receive link, and its stability directly determines the radiation correction accuracy. The hardware link includes the transmitter, power amplifier, waveguide, antenna, and receiver, and the calculation formula is as follows: ; in, For transmit link gain, To receive link gain, This represents the total loss.

[0066] SAR signal processing introduces gain variations, which need to be accurately modeled to ensure radiometric correction accuracy. The processing chain gain originates from signal compression, filtering, multi-look operations, etc., and the gain characteristics of each step are shown in the table below:

[0067] External calibration parameters are a key technology for calibrating SAR systems using ground targets with known scattering characteristics (such as corner reflectors). The core of this technology is to deduce external calibration parameters from the theoretical radar cross-section (RCS) of the point target. The main steps are as follows: deploy corner reflectors within the SAR imaging range, measure their precise coordinates, acquire SAR images containing the target, extract the target's DN value, and combine it with the slant range. ,wavelength Parameters, reverse calculation Value. The point target calibration formula is as follows: ; The theoretical RCS is calculated differently for different point targets. For a trihedral reflector, the theoretical RCS is: ,in, Let be the side length of the corner reflector.

[0068] Furthermore, the steps for constructing the antenna pattern compensation factor based on the two-dimensional lookup table include: Obtain real-time geometric parameters; Use the real-time geometric parameters as input parameters to search the two-dimensional lookup table for the corresponding real-time geometric parameters; The antenna pattern compensation factor is obtained based on the input parameters.

[0069] In the above implementation process, the input parameters corresponding to the two-dimensional lookup table are found according to the real-time geometric parameters to further obtain the antenna pattern compensation factor, ensuring the accuracy of the antenna pattern compensation factor and simplifying the calculation process.

[0070] The formula for calculating the antenna pattern compensation factor is as follows: ; in, The maximum gain at the beam center is typically chosen as the reference gain. , This refers to the antenna gain during transmission. This represents the antenna gain during reception.

[0071] The LUT uses real-time geometric parameters (azimuth and elevation angles) as indexes to store the fitted and sampled gain compensation coefficients. During the imaging process, the LUT is queried based on the real-time geometric parameters of each pixel to calculate the antenna pattern compensation factor and achieve real-time correction.

[0072] This application represents a radical architectural revolution, decomposing the radiometric correction factor and deeply embedding it into the inherent computational steps of the CS imaging algorithm. Under this architecture, correction is no longer an independent process following imaging, but rather an organic whole that occurs synchronously with and is integrated with the geometric focusing process.

[0073] Example 2 To implement the method corresponding to Embodiment 1 above and achieve the corresponding functional and technical effects, an on-orbit radiation correction device for a spaceborne synthetic aperture radar is provided below, such as... Figure 2 As shown, the device includes: Acquisition module 1 is used to acquire echo data from synthetic aperture radar and to acquire the first antenna pattern; Preprocessing module 2 is used to preprocess the echo data to obtain preprocessed echo data; Compression module 3 is used to compress the radiation pattern of the first antenna to obtain a two-dimensional lookup table; Module 4 is used to construct the comprehensive compensation factor based on the two-dimensional lookup table; Module 5 is introduced to incorporate the comprehensive compensation factor into the pre-built first imaging model to obtain the second imaging model. Imaging module 6 is used to input the preprocessed echo data into the second imaging model to obtain target echo data.

[0074] In the above implementation process, the antenna pattern is compressed to reduce its storage space, and a comprehensive compensation factor is constructed. The echo data of the synthetic aperture radar is corrected before imaging, simplifying the processing flow, reducing the consumption of computing resources, improving accuracy while shortening the time consumption, and improving imaging efficiency.

[0075] Furthermore, preprocessing module 2 is also used for: The echo data is de-DCed using the sliding window mean algorithm to obtain the echo data after de-DCing. Construct the scan gain factor; The echo data after DC removal operation is corrected by scanning gain factor to obtain the echo data after scanning gain correction. The echo data after scanning gain correction is determined to be the preprocessed echo data.

[0076] In the above implementation process, by performing DC removal on the echo data and constructing a scanning gain factor to correct its scanning gain, the echo data can be preprocessed before imaging, improving the accuracy of the echo data and providing data support for the subsequent imaging process.

[0077] Furthermore, preprocessing module 2 is also used to construct the scan gain factor, with the following formula: ; in, Maximum gain at the beam center It is the off-axis angle. The attenuation coefficient is... This is the scan gain factor.

[0078] In the above implementation process, the scanning gain factor is calculated based on the maximum gain at the beam center, the off-axis angle, and the attenuation coefficient. This compensates for the gain attenuation caused by the change in the depression angle in the range direction, significantly reduces the dynamic range pressure of subsequent processing, and avoids the risk of numerical overflow in post-processing compensation.

[0079] Furthermore, preprocessing module 2 is also used to perform DC removal on the echo data according to the sliding window averaging algorithm, to obtain the DC-removed echo data, as shown in the formula: ; Where N is the number of samples within the sliding window, and S is the echo data. This represents the echo data after DC removal, where t is the azimuth time and i is the index of the sample within the sliding window. For distance to time, For the first in the sliding window The time corresponding to each sample.

[0080] In the above implementation process, performing DC removal on the echo data can effectively eliminate the DC bias of the system and improve the dynamic range of signal processing.

[0081] Furthermore, compression module 3 is also used for: By capturing key parameters of the first antenna pattern, the second antenna pattern can be obtained; The second antenna pattern is subjected to grid sparsification to obtain a two-dimensional lookup table.

[0082] In the above implementation process, capturing key parameters of the first antenna pattern can effectively extract the physical characteristics in the first antenna pattern. Then, the extracted physical characteristics can be compressed to reduce the storage space of the antenna pattern, thus providing support for improving the real-time performance of the correction.

[0083] Furthermore, compression module 3 is also used to capture key parameters of the first antenna pattern to obtain the second antenna pattern, as shown in the formula: ; in, It is the azimuth angle. The pitch angle, Antenna length For wavelength, The peak value corresponding to the first antenna pattern. This is the second antenna direction chart, and sinc() is the Singer function.

[0084] In the above implementation process, by capturing key parameters based on the peak value of the first antenna pattern and multiple geometric parameters, the physical and mathematical characteristics of the antenna pattern can be captured, the key features of the antenna pattern can be extracted, and data redundancy can be reduced.

[0085] Furthermore, Module 4 is also used for: Construct the antenna pattern compensation factor based on a two-dimensional lookup table; Construct system gain, processing chain gain, and external calibration parameters; Obtain the third factor in the range-Doppler domain of the first imaging model; The third factor is adjusted based on the antenna pattern compensation factor, system gain, processing chain gain, and external calibration parameters to obtain the comprehensive compensation factor.

[0086] In the above implementation process, the third factor is adjusted according to the antenna pattern compensation factor, system gain, processing chain gain and external calibration parameters to obtain the comprehensive compensation factor, which can adjust the system gain, ensure the accuracy of radiation correction, and further improve the radiation uniformity and realism of the imaging.

[0087] Furthermore, Module 4 is also used for: Obtain real-time geometric parameters; Use the real-time geometric parameters as input parameters to search the two-dimensional lookup table for the corresponding real-time geometric parameters; The antenna pattern compensation factor is obtained based on the input parameters.

[0088] In the above implementation process, the input parameters corresponding to the two-dimensional lookup table are found according to the real-time geometric parameters to further obtain the antenna pattern compensation factor, ensuring the accuracy of the antenna pattern compensation factor and simplifying the calculation process.

[0089] The aforementioned on-orbit radiation correction device for spaceborne synthetic aperture radar can implement the method described in Embodiment 1. The options described in Embodiment 1 also apply to this embodiment, and will not be detailed here.

[0090] The remaining contents of this embodiment can be referred to the contents of Embodiment 1 above, and will not be repeated in this embodiment.

[0091] Example 3 This application provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor runs the computer program to enable the electronic device to perform the on-orbit radiation correction method for a spaceborne synthetic aperture radar according to Embodiment 1.

[0092] Alternatively, the aforementioned electronic device may be a server.

[0093] Please see Figure 3 , Figure 3 This is a schematic diagram illustrating the structural composition of an electronic device provided in an embodiment of this application. The electronic device may include a processor 31, a communication interface 32, a memory 33, and at least one communication bus 34. The communication bus 34 is used to enable direct communication between these components.

[0094] Optionally, the electronic device may also include a storage controller and an input / output unit. The memory 33, storage controller, processor 31, peripheral interface, and input / output unit are electrically connected to each other directly or indirectly to realize data transmission or interaction.

[0095] Input / output units are used to enable users to create tasks and set optional start periods or preset execution times for those tasks, facilitating user-server interaction. Input / output units can be, but are not limited to, a mouse and keyboard.

[0096] Understandable. Figure 3 The structure shown is for illustrative purposes only; the electronic device may also include components that are more advanced than those shown. Figure 3 The more or fewer components shown, or having the same Figure 3 Different configurations are shown. Additionally, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the on-orbit radiation correction method for spaceborne synthetic aperture radar as described in Embodiment 1.

[0097] This application also provides a computer program product that, when run on a computer, causes the computer to perform the method described in the method embodiment.

[0098] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0099] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of protection of the claims.

Claims

1. A method for on-orbit radiation correction of a spaceborne synthetic aperture radar, characterized in that, The method includes: Acquire echo data from synthetic aperture radar and obtain the first antenna pattern; The echo data is preprocessed to obtain preprocessed echo data; The first antenna pattern is compressed to obtain a two-dimensional lookup table; Construct a comprehensive compensation factor based on the two-dimensional lookup table; The comprehensive compensation factor is introduced into the pre-constructed first imaging model to obtain the second imaging model; The preprocessed echo data is input into the second imaging model to obtain the target echo data.

2. The on-orbit radiation correction method for spaceborne synthetic aperture radar according to claim 1, characterized in that, The step of preprocessing the echo data to obtain preprocessed echo data includes: The echo data is de-DC operated according to the sliding window mean algorithm to obtain the echo data after de-DC operation; Construct the scan gain factor; The echo data after DC removal operation is scanned and corrected according to the scan gain factor to obtain the scan gain corrected echo data. The echo data after scanning gain correction is determined to be the preprocessed echo data.

3. The on-orbit radiation correction method for spaceborne synthetic aperture radar according to claim 2, characterized in that, The formula for constructing the scan gain factor is: ； in, Maximum gain at the beam center It is the off-axis angle. The attenuation coefficient is... The scan gain factor is mentioned above.

4. The on-orbit radiation correction method for spaceborne synthetic aperture radar according to claim 2, characterized in that, The formula for performing DC removal on the echo data using the sliding window averaging algorithm to obtain the DC-removed echo data is as follows: ； Where N is the number of samples within the sliding window, and S is the echo data. The echo data after the DC removal operation is given, where t is the azimuth time and i is the index of the sample within the sliding window. For distance to time, For the first in the sliding window The time corresponding to each sample.

5. The on-orbit radiation correction method for spaceborne synthetic aperture radar according to claim 1, characterized in that, The step of compressing the first antenna pattern to obtain a two-dimensional lookup table includes: By capturing key parameters of the first antenna pattern, the second antenna pattern is obtained; The second antenna pattern is subjected to mesh sparsification to obtain the two-dimensional lookup table.

6. The on-orbit radiation correction method for spaceborne synthetic aperture radar according to claim 5, characterized in that, The formula for obtaining the second antenna pattern by capturing key parameters of the first antenna pattern is as follows: ； in, It is the azimuth angle. The pitch angle, Antenna length For wavelength, The peak value corresponding to the first antenna pattern. Let sinc() be the second antenna pattern.

7. The on-orbit radiation correction method for spaceborne synthetic aperture radar according to claim 1, characterized in that, The step of constructing the comprehensive compensation factor based on the two-dimensional lookup table includes: Construct the antenna pattern compensation factor based on the two-dimensional lookup table; Construct system gain, processing chain gain, and external calibration parameters; Obtain the third factor in the range-Doppler domain of the first imaging model; The third factor is adjusted based on the antenna pattern compensation factor, the system gain, the processing chain gain, and the external calibration parameters to obtain the comprehensive compensation factor.

8. The on-orbit radiation correction method for spaceborne synthetic aperture radar according to claim 7, characterized in that, The step of constructing the antenna pattern compensation factor based on the two-dimensional lookup table includes: Obtain real-time geometric parameters; The real-time geometric parameters are used as an index to look up the input parameters corresponding to the real-time geometric parameters in the two-dimensional lookup table; The antenna pattern compensation factor is obtained based on the input parameters.

9. An on-orbit radiation correction device for a spaceborne synthetic aperture radar, characterized in that, The device includes: The acquisition module is used to acquire echo data from the synthetic aperture radar and to acquire the first antenna pattern. The preprocessing module is used to preprocess the echo data to obtain preprocessed echo data; A compression module is used to compress the radiation pattern of the first antenna to obtain a two-dimensional lookup table; The construction module is used to construct a comprehensive compensation factor based on the two-dimensional lookup table; An introduction module is used to introduce the comprehensive compensation factor into a pre-constructed first imaging model to obtain a second imaging model; An imaging module is used to input the preprocessed echo data into the second imaging model to obtain target echo data.

10. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in claims 1-8.

11. A storage medium, characterized in that, The storage medium stores instructions that, when executed on a computer, cause the computer to perform the method as described in claims 1-8.

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