Satellite-borne SAR imaging method and device, storage medium and equipment

Abstract

The invention provides a satellite-borne SAR imaging method and device, a storage medium and equipment, and the method comprises the steps: carrying out the coarse imaging through employing an echo signal of a satellite-borne SAR, selecting a plurality of sub-regions from an image after coarse imaging, estimating the Doppler frequency of each sub-region, and carrying out the Doppler frequency of each sub-region, according to the method, the azimuth space-variant rate of the Doppler frequency modulation rate is solved by using a least square method, then an NCS parameter is obtained, and space-variant correction and imaging processing are performed on echo signals by using the NCS parameter and using an NCS method, so that an image with a good focusing effect is obtained. Therefore, by using the least square method and combining with the Doppler frequency modulation rates of multiple regions, the azimuth space-variant rate estimation of the Doppler frequency modulation rates is carried out, and then the NCS parameters are accurately estimated, so that the center point and the azimuth edge point of the final imaging result can realize a good focusing effect, and the scene edge imaging effect is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of space-borne synthetic aperture radar, in particular to a space-borne SAR imaging method, device, storage medium and equipment. BACKGROUND

[0002] The space-borne synthetic aperture radar (SAR) is an active remote sensing device carried on a satellite, which realizes all-weather and all-day imaging of the ground surface by transmitting and receiving microwave signals, and provides rich data support for the research and application of geology, environment, agriculture and other fields. The lunar-orbiting space-borne SAR is a SAR system carried on a lunar-orbiting satellite, which can realize high-resolution imaging of places with poor light conditions such as the bottom of a meteorite crater and the back of a crater, and can also detect the lunar soil or underground conditions by using the penetration characteristics of electromagnetic waves, which has important significance for lunar exploration. The lunar-orbiting satellite cannot achieve accurate positioning by means of a satellite positioning network, and there is a problem of low measurement accuracy of attitude and orbit information. Low measurement accuracy of attitude and orbit information can easily lead to errors in the Doppler frequency modulation, thereby reducing the imaging quality, so it is necessary to estimate and correct the errors in the Doppler frequency modulation.

[0003] At present, the MD (Map Drift) method is generally used to estimate the Doppler frequency modulation in the related art. This method decomposes the azimuth signal of the SAR echo into two sub-views, calculates the deviation of the two sub-views, and estimates the accurate Doppler frequency modulation. However, when the lunar-orbiting satellite is in an elliptical orbit with a large eccentricity, the azimuth variation of the Doppler frequency modulation is serious. The MD method uniformly estimates the Doppler frequency modulation of the whole scene without considering the azimuth variation of the Doppler frequency modulation, so it is easy to cause the imaging effect of the scene edge to decrease. SUMMARY

[0004] The purpose of the present application is to provide a space-borne SAR imaging method, device, storage medium and equipment, which aims to solve the problem that the related art lunar-orbiting space-borne SAR imaging method does not consider the azimuth variation of the Doppler frequency modulation, which easily leads to a decrease in the imaging effect of the scene edge.

[0005] In a first aspect, the present application provides a space-borne SAR imaging method, which comprises: processing the echo signal of a space-borne SAR to obtain a preliminary focused image; selecting a plurality of sub-regions in the preliminary focused image, estimating the Doppler frequency modulation of each sub-region, and based on the estimation result, using the least squares method to solve the azimuth variation rate of the Doppler frequency modulation; calculating the NCS parameter according to the azimuth variation rate, and performing azimuth variation correction and imaging processing on the echo signal according to the NCS parameter to obtain a target image.

[0006] In the above implementation process, coarse imaging is performed using the echo signal from spaceborne SAR. Multiple sub-regions are selected within the coarsely imaged image, and the Doppler modulation frequency (DMC) of each sub-region is estimated. Using the DMC of each sub-region, the azimuth spatial variation rate of the DMC is solved using the least squares method, thus obtaining the NCS parameters. Then, using the NCS parameters, the echo signal is spatially corrected and processed using the NCS method, resulting in an image with good focusing effect. In this way, by using the least squares method in conjunction with the DMC of multiple regions to estimate the azimuth spatial variation rate of the DMC, and then accurately estimating the NCS parameters, the center point and azimuth edge points of the final imaging result can achieve good focusing effect, improving the scene edge imaging effect.

[0007] Furthermore, in some examples, before processing the echo signal of the spaceborne SAR, the process includes: establishing a polynomial slant range model of the spaceborne SAR; and obtaining the relationship between the NCS parameters and the azimuth spatial variation of the second expansion term of the slant range history of the spaceborne SAR based on the polynomial slant range model.

[0008] In the above implementation process, when the spaceborne SAR is in an elliptical orbit, a polynomial slant range model is used to describe the slant range history. This polynomial slant range model is used to analyze the relationship between the NCS parameters and the azimuth spatial variation of the second expansion term of the slant range history of the spaceborne SAR. Thus, the estimation of the NCS parameters is transformed into the estimation of the azimuth spatial variation of the second expansion term of the slant range history.

[0009] Furthermore, in some examples, the polynomial slant distance model is expressed as the following formula:

[0010] in, For a zero Doppler time is The corresponding slope distance is The slant distance history corresponding to the point target; Location and time; and These are the polynomial coefficients; The polynomial coefficients are expressed by the following formula:

[0011] in, For polynomial coefficients, ; For reference target The first slant range history One expansion item; For the first The distance spatial variation of each expanded term; For the first The azimuth variation part of each expanded item.

[0012] In the above implementation process, Taylor expansion is used to expand the complex slant range history into a polynomial form, and then the polynomial coefficients are further expanded, so as to more accurately analyze the relationship between NCS parameters and Doppler modulation frequency.

[0013] Furthermore, in some examples, the relationship between the NCS parameters and the azimuth spatial variation of the second expansion term of the slant range history of the spaceborne SAR is expressed based on the following formula:

[0014] In the formula, The NCS parameters; The radar wavelength of the spaceborne SAR; The azimuth spatial variation is the second expansion term of the slant range history of the spaceborne SAR.

[0015] In the above implementation process, a specific representation of the relationship between NCS parameters and the azimuth spatial variation of the second expansion term of the slant range history of the spaceborne SAR is provided. In this way, the NCS parameters can be accurately estimated by estimating the azimuth spatial variation of the second expansion term of the slant range history.

[0016] Furthermore, in some examples, selecting multiple sub-regions in the preliminary focused image includes: dividing the preliminary focused image into multiple candidate regions using a two-dimensional sliding window; calculating the contrast of each candidate region; and selecting several sub-regions from the multiple candidate regions based on the contrast.

[0017] In the above implementation process, contrast is used as the criterion for sub-region selection. A two-dimensional sliding window operation is performed on the coarse imaging results to calculate the contrast of each candidate region. Several candidate regions are then selected as sub-regions for subsequent Doppler frequency modulation estimation. Thus, by selecting sub-regions with higher imaging quality, the accuracy of Doppler frequency modulation estimation can be improved.

[0018] Furthermore, in some examples, estimating the Doppler modulation frequency of each sub-region includes: using the maximum contrast method to estimate the Doppler modulation frequency of each selected sub-region, thereby obtaining the estimated Doppler modulation frequency value corresponding to the sub-region.

[0019] In the above implementation process, a specific method is provided for accurately estimating the Doppler modulation frequency of each sub-region.

[0020] Furthermore, in some examples, the step of using the least squares method to solve for the azimuth spatial variation rate of the Doppler frequency modulation (FCM) based on the estimation results includes: obtaining polynomial coefficients for the multiple sub-regions based on the FCM estimates for the multiple sub-regions; constructing an objective function based on the polynomial coefficients for the multiple sub-regions; the objective function representing the functional relationship between the polynomial coefficients and the azimuth spatial variation rate and range spatial variation rate of the FCM; converting the objective function into a matrix equation, and solving the matrix equation using the least squares method to obtain the azimuth spatial variation rate of the FCM.

[0021] In the above implementation process, a specific method is provided to estimate the azimuth spatial variation rate of the Doppler frequency using the least squares method and by combining the Doppler frequency modulation of multiple sub-regions.

[0022] Furthermore, in some examples, the matrix equation is expressed as:

[0023] in, for The vector form of ; For the first Polynomial coefficients of each subregion , The total number of the multiple sub-regions; For the first The zero Doppler time corresponding to the Doppler modulation frequency estimate of each sub-region The slant range corresponding to the zero Doppler time; The azimuth spatial variation rate of the Doppler modulation frequency; The distance spatial variation rate is the frequency of the Doppler modulation.

[0024] In the above implementation process, a specific representation of matrix equations is provided, which transforms the problem of finding the azimuth spatial variation rate of the Doppler modulation frequency into a problem of solving matrix equations.

[0025] Furthermore, in some examples, the NCS parameter is calculated based on the following formula:

[0026] In the formula, The azimuth spatial variation rate of the Doppler modulation frequency.

[0027] In the above implementation process, a specific method is provided for calculating NCS parameters based on the azimuth spatial variation rate of the Doppler modulation frequency.

[0028] Secondly, this application provides a spaceborne SAR imaging device, comprising: a processing module for processing the echo signal of the spaceborne SAR to obtain a preliminary focused image; a solving module for selecting multiple sub-regions in the preliminary focused image, estimating the Doppler modulation frequency of each sub-region, and solving the azimuth spatial variation rate of the Doppler modulation frequency using the least squares method based on the estimation results; and a correction module for calculating NCS parameters according to the azimuth spatial variation rate, and performing spatial variation correction and imaging processing on the echo signal according to the NCS parameters to obtain a target image.

[0029] Thirdly, this application provides an electronic device comprising: 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 steps of the method described in any of the first aspects.

[0030] Fourthly, this application provides 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.

[0031] Fifthly, this application provides a computer program product that, when run on a computer, causes the computer to perform the method described in any of the first aspects.

[0032] Other features and advantages disclosed in this application 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 above-described technology disclosed in this application.

[0033] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0034] 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 of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 A flowchart of a spaceborne SAR imaging method provided in this application embodiment; Figure 2 A schematic diagram illustrating the workflow of a lunar orbiting satellite SAR azimuth NCS parameter estimation scheme provided in this application embodiment; Figure 3 A schematic diagram of a lunar orbiting SAR space configuration provided for an embodiment of this application; Figure 4 A schematic diagram of the scene and dot matrix setup in a lunar orbiting satellite-borne SAR simulation experiment provided in this application embodiment; Figure 5 A schematic diagram illustrating the satellite velocity error in a lunar orbiting satellite-borne SAR simulation experiment provided in this application embodiment; Figure 6 A schematic diagram illustrating the three-dimensional position error in a lunar orbiting satellite-borne SAR simulation experiment provided in this application embodiment; Figures 7(a), 7(b), 7(c), 7(d), and 7(e) are schematic diagrams of two-dimensional contour maps of points A, B, C, D, and E in a lunar orbiting satellite SAR simulation experiment provided in the embodiments of this application, without parameter estimation. Figures 8(a), 8(b), 8(c), 8(d), and 8(e) are schematic diagrams of two-dimensional contour maps of points A, B, C, D, and E in a lunar orbiting satellite SAR simulation experiment provided in the embodiments of this application, under the condition of parameter estimation. Figure 9 A block diagram of a spaceborne SAR imaging device provided in an embodiment of this application; Figure 10 This is a structural block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0036] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0037] 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.

[0038] SAR systems possess advantages such as large imaging range, all-weather operation, and all-time coverage, and are widely used in environmental monitoring, resource exploration, and marine observation. Lunar-orbiting satellite-borne SAR systems, carried on lunar orbiting satellites, are of great significance for lunar exploration. Lunar orbiting satellites cannot achieve precise positioning using satellite positioning networks, resulting in low accuracy in attitude and orbit information measurement. This low accuracy easily leads to errors in Doppler frequency modulation (FCM), thus reducing image quality. Therefore, FCM error estimation and correction are necessary. Currently, the MD method is generally used to estimate the FCM. This method decomposes the azimuth signal of a SAR echo into two sub-views. The signals in the two sub-views have the same second phase and opposite first phases. The difference in the first phase causes a deviation in the position of the compressed signal, and this deviation is related to the FCM. Therefore, by calculating the deviation between the two sub-views, the accurate FCM can be estimated. However, when a lunar satellite is in an elliptical orbit with a large orbital eccentricity, the azimuth variation of the Doppler frequency modulation is severe. The MD method makes a uniform estimate of the Doppler frequency modulation for the entire scene without considering the azimuth variation of the Doppler frequency modulation, which can easily lead to a decrease in the imaging effect at the scene edges.

[0039] To address the aforementioned problems, this application provides a spaceborne SAR imaging scheme. It utilizes the echo signal from the spaceborne SAR for coarse imaging. Multiple sub-regions are selected within the coarsely imaged region, and the Doppler modulation frequency (DMC) of each sub-region is estimated. Using the DMC of each sub-region, the azimuth spatial variation rate of the DMC is calculated using the least squares method, thereby obtaining the NCS parameters. Then, using the NCS parameters, the echo signal is spatially corrected and processed using the NCS method, resulting in an image with better focusing. Thus, by using the least squares method in conjunction with the DMC of multiple regions to estimate the azimuth spatial variation rate of the DMC, and then accurately estimating the NCS parameters, the final imaging result achieves good focusing at the center point and azimuth edge points.

[0040] The embodiments of this application will be described below: like Figure 1 As shown, Figure 1 This is a flowchart of a spaceborne SAR imaging method provided in an embodiment of this application. The method includes: Step 101: Process the echo signal of the spaceborne SAR to obtain a preliminary focused image; The spaceborne SAR mentioned in this step can refer to lunar-orbiting spaceborne SAR or SAR systems mounted on other satellites in elliptical orbits. Taking lunar-orbiting spaceborne SAR as an example, when a lunar satellite is in an elliptical orbit with a large orbital eccentricity, the azimuth variation of the Doppler frequency modulation (FCM) is severe. It is necessary to introduce NCS parameters through the NCS (Nonlinear Chirp Scaling) method to correct for the azimuth variation in order to obtain better imaging results. The NCS method is an azimuth variation correction algorithm that uses a higher-order scaling function to handle complex azimuth variation characteristics. The MD method does not estimate the NCS parameters, and attitude and orbit information errors can also lead to errors in the NCS parameters, resulting in incorrect Doppler FCM correction. Therefore, this embodiment uses the least squares method to estimate the azimuth variation rate of the Doppler frequency modulation, thereby achieving accurate estimation of the NCS parameters, which is applicable to the field of lunar-orbiting spaceborne SAR imaging.

[0041] To achieve NCS parameter estimation, coarse imaging is first performed using echo data from spaceborne SAR. During implementation, range migration correction, range compression, and azimuth compression can be applied to the echo data to obtain a pre-focused image.

[0042] In some embodiments, prior to this step, the following may be included: establishing a polynomial slant range model for the spaceborne SAR; and obtaining the relationship between the NCS parameters and the azimuth spatial variation of the second-order expansion term of the slant range history of the spaceborne SAR based on the polynomial slant range model. That is, when the spaceborne SAR is in an elliptical orbit, a polynomial slant range model can be used to describe the slant range history. This polynomial slant range model is then used to analyze the relationship between the NCS parameters and the azimuth spatial variation of the second-order expansion term of the slant range history, thereby converting the estimation of the NCS parameters into an estimation of the azimuth spatial variation of the second-order expansion term of the slant range history.

[0043] Optionally, the polynomial slant distance model can be expressed as the following formula:

[0044] in, For a zero Doppler time is The corresponding slope distance is The slant distance history corresponding to the point target; Location and time; and These are the polynomial coefficients; The polynomial coefficients can be expressed by the following formula:

[0045] in, For polynomial coefficients, ; For reference target The first slant range history One expansion item; For the first The distance spatial variation of each expanded term; For the first The azimuth spatial variation part of each expansion term. In other words, the complex slant range history is expanded into a polynomial form using Taylor expansion, and then the polynomial coefficients are further expanded, thereby enabling a more accurate analysis of the relationship between NCS parameters and Doppler modulation frequency.

[0046] Combining the previous formula, the Doppler modulation frequency can be expressed as: In the formula is the radar wavelength of the spaceborne SAR. To correct for the azimuth spatial variation of the Doppler frequency modulation, the NCS method is required, and the following NCS function is introduced: In the formula Represents the imaginary unit. For NCS parameters, Let be time, where the NCS parameter is related to the azimuth spatial variation rate of the Doppler modulation frequency. Optionally, the relationship between the NCS parameter and the azimuth spatial variation of the second expansion term of the slant range history of the spaceborne SAR can be expressed based on the following formula:

[0047] In the formula, This represents the azimuth spatial variation of the second expansion term of the slant range history of the spaceborne SAR. Thus, the NCS parameters can be accurately estimated by estimating the azimuth spatial variation of the second expansion term of the slant range history.

[0048] Step 102: Select multiple sub-regions in the preliminary focused image, estimate the Doppler modulation frequency of each sub-region, and based on the estimation results, use the least squares method to solve the azimuth spatial variation rate of the Doppler modulation frequency. This step refers to: after completing the coarse imaging, selecting N (N≥3) sub-regions, performing Doppler frequency modulation estimation on the selected N sub-region images to obtain N Doppler frequency modulation estimates, and then using the least squares method to combine the Doppler frequency modulation estimates of the N sub-regions to perform azimuth spatial variation estimation of the Doppler frequency modulation.

[0049] In some embodiments, selecting multiple sub-regions from the preliminary focused image mentioned in this step may include: dividing the preliminary focused image into multiple candidate regions using a two-dimensional sliding window; calculating the contrast of each candidate region; and selecting several sub-regions from the multiple candidate regions based on the contrast. That is, using contrast as the criterion for sub-region selection, a two-dimensional sliding window operation is performed on the coarse imaging result to calculate the contrast of each candidate region, and selecting several candidate regions with the highest contrast as sub-regions for subsequent Doppler frequency modulation estimation. Thus, by selecting sub-region images with higher imaging quality, the accuracy of Doppler frequency modulation estimation can be improved. Of course, in other embodiments, image quality evaluation metrics such as signal-to-noise ratio, sharpness, or feature-to-noise ratio can also be used to select sub-regions.

[0050] In some embodiments, estimating the Doppler modulation frequency (DMC) of each sub-region mentioned in this step may include: using the maximum contrast method to estimate the DMC of each selected sub-region, thereby obtaining the estimated DMC value corresponding to the sub-region. That is, for the selected N sub-region images, the maximum contrast is used as the criterion for DMC estimation. When the image contrast reaches its maximum value, the image is considered to be well-focused, and the DMC value at this point is determined as the estimated DMC value. In this way, the DMC of each sub-region can be accurately estimated. Of course, in other embodiments, other algorithms, such as gradient descent autofocus, can also be used for DMC estimation.

[0051] Further, in some embodiments, the step of solving the azimuth spatial variation rate of the Doppler frequency modulation (FCM) using the least squares method based on the estimation results mentioned in this step may include: obtaining polynomial coefficients for the multiple sub-regions based on the FCM estimates for the multiple sub-regions; constructing an objective function based on the polynomial coefficients for the multiple sub-regions; the objective function representing the functional relationship between the polynomial coefficients and the azimuth spatial variation rate and range spatial variation rate of the FCM; converting the objective function into a matrix equation, and solving the matrix equation using the least squares method to obtain the azimuth spatial variation rate of the FCM. In other words, after obtaining the FCM estimates for N sub-regions, the polynomial coefficients corresponding to the N sub-regions can be obtained, and then the objective function can be constructed using these coefficients, i.e., the objective function represents the relationship between the polynomial coefficients and the azimuth spatial variation rate of the FCM. and distance space variation rate The functional relationship between them is used to transform the objective function into a matrix equation, thereby enabling the determination of the objective function. The problem is transformed into a matrix equation problem. Based on this, the least squares method is used to solve the problem, which can quickly and accurately obtain the azimuth spatial variation rate of the Doppler modulation frequency.

[0052] Assume the total number of sub-regions is Then the first The polynomial coefficients of each subregion can be expressed as... , , The zero Doppler time corresponding to the Doppler modulation frequency estimate of this sub-region. Let be the slant range corresponding to this zero Doppler time, then the objective function can be expressed as:

[0053] Converting the objective function into matrix form yields the matrix equation shown below:

[0054] in, for The vector form of is used. Correspondingly, the process of solving using the least squares method can be expressed as:

[0055] This formula allows for a quick and accurate solution. .

[0056] Step 103: Calculate the NCS parameters based on the azimuth spatial variation rate, and perform spatial variation correction and imaging processing on the echo signal based on the NCS parameters to obtain the target image.

[0057] In this embodiment, after solving for the azimuth spatial variation rate of the Doppler modulation frequency, the NCS parameters can be calculated based on the relationship between the NCS parameters and the azimuth spatial variation rate of the Doppler modulation frequency. Then, the NCS method is used for spatial variation correction and imaging processing to obtain a target image with good focusing effect.

[0058] In implementation, azimuth space variation rate The azimuth variation of the second expansion term of the slant range history The relationship can be represented as Therefore, in some embodiments, the NCS parameter can be calculated based on the following formula:

[0059] Thus, the calculated azimuth spatial variation rate Substituting these values ​​into the formula will quickly yield the NCS parameters.

[0060] In this embodiment, coarse imaging is performed using echo signals from spaceborne SAR. Multiple sub-regions are selected within the coarsely imaged data, and the Doppler modulation frequency (DMC) of each sub-region is estimated. Using the DMC of each sub-region, the azimuth spatial variation rate of the DMC is calculated using the least squares method, thus obtaining the NCS parameters. Then, using the NCS parameters, the echo signal is spatially corrected and processed using the NCS method, resulting in an image with good focusing. Thus, by using the least squares method in conjunction with the DMC of multiple regions to estimate the azimuth spatial variation rate of the DMC, and then accurately estimating the NCS parameters, the center point and azimuth edge points of the final imaging result achieve good focusing, improving the scene edge imaging effect.

[0061] To provide a more detailed explanation of the solution in this application, a specific embodiment is described below: This embodiment provides a scheme for estimating the azimuth NCS parameters of lunar-orbiting satellite-borne SAR to solve the problem of estimating the azimuth spatial transformation imaging parameters of lunar-orbiting satellite-borne SAR. The workflow of this scheme is as follows: Figure 2 As shown, it includes: S201, Constructing a lunar orbiting satellite-borne SAR space configuration; Specifically, the space configuration of lunar-borne SARs is as follows: Figure 3 As shown, where, and These are the satellite position vector and the target position vector, respectively. Let be the distance vector between the satellite and the target; the true slant range history of a lunar-orbiting SAR can be expressed as:

[0062] Since the lunar satellite is in an elliptical orbit, equation (1) is quite complex and cannot be directly applied to the algorithm. Therefore, it can be represented using Taylor representation. In implementation, for a zero Doppler time... The corresponding slope distance is The slant range history of a point target can be expressed using a Taylor expansion as follows:

[0063] in, Location and time; For each polynomial coefficient It can also be expanded as:

[0064] in, Indicates reference target The first slant range history One expansion item; Indicates the first The distance spatial variation of each expanded term; Indicates the first The azimuth variable part of each expanded item; According to equations (2) and (3), the Doppler modulation frequency can be expressed as:

[0065] As shown in equation (4), the Doppler frequency modulation exhibits two-dimensional spatial variation, making it impossible to directly estimate using traditional error estimation methods. To correct the azimuth spatial variation of the Doppler frequency modulation, the NCS method is required, and the following NCS function is introduced:

[0066] Among them, NCS parameters The azimuth spatial variation rate, which is related to the Doppler modulation frequency, can be expressed as:

[0067] From equation (6), it can be seen that for the NCS parameters The estimate can be transformed into the azimuth space variation of the second expansion term of the slant range history. The estimate; S202, coarse imaging; Specifically, the echo data from lunar-borne SAR undergoes RCMC (Range Migration Correction) and range compression, followed by azimuth compression using polynomial coefficients with errors to obtain a coarsely focused image. The signal after RCMC and range compression can be expressed as:

[0068] in, Indicates the azimuth frequency. Indicates distance to time. Indicates the shortest slope distance. Represents the speed of light. This represents the signal envelope after distance compression. It can be represented as:

[0069] The signal after azimuth compression using polynomial coefficients with errors can be expressed as:

[0070] in, This represents the inverse Fourier transform of the orientation. Equation (9) shows that when there is an error in the polynomial coefficients, the imaging result has a quadratic phase error, leading to image defocusing. S203, Sub-region selection; Specifically, after completing the coarse imaging, N (N≥3) sub-regions can be selected, and the Doppler modulation frequency of each sub-region can be estimated using the maximum contrast method. To improve the accuracy of the Doppler modulation frequency estimation, the selected sub-region images need to have high imaging quality; therefore, contrast is used as the criterion for selecting sub-region images. The formula for calculating image contrast is:

[0071] in, This indicates taking the average value. Indicates the modulo value. The selected sub-region is represented by Equation (10). A two-dimensional sliding window operation is performed on the coarse imaging results to calculate the contrast of each region, and several regions with the highest contrast are selected as sub-regions for subsequent Doppler frequency modulation estimation. S204, Doppler frequency modulation estimation; Specifically, based on the results of coarse imaging processing and sub-region selection, the Doppler frequency modulation estimation is performed on the N sub-region images obtained by screening, using the maximum contrast as the criterion, so that N different Doppler frequency modulation estimates can be obtained. According to equation (9), when At this point, the image can achieve good focus, and the image contrast reaches its maximum value. To distinguish between different images, this estimated value is denoted as... ,Right now Repeat this estimation process on N sub-regions to obtain the polynomial coefficients corresponding to the N sub-regions. ,in ; S205 and NCS parameter estimation; Specifically, the azimuth spatial variation rate and range spatial variation rate of the Doppler modulation frequency are respectively denoted as... and Then, for any subregion, the Doppler modulation frequency can be expressed as:

[0072] Rewriting equation (10) in matrix form, we get:

[0073] in, for The vector form of is used to obtain . Transform the problem into a matrix equation problem, since the matrix Since the generalized inverse matrix is ​​irreversible and cannot be directly calculated, and calculating the generalized inverse matrix would cause inconvenience to hardware design, this embodiment uses the least squares method for solution. The process of solving using the least squares method can be expressed as:

[0074] in, Representation matrix The transpose of the matrix; This represents the matrix inversion. It is obtained by solving equation (13). Then, combining with equation (6), the NCS parameters can be obtained as follows:

[0075] Once the NCS parameters are obtained, the azimuth NCS method can be used for spatial variation correction and subsequent imaging.

[0076] To verify the effectiveness of the above scheme, a lunar-orbiting satellite-borne SAR simulation experiment was conducted. In the implementation, the radar operated in strip mode, with a resolution set to 0.8m (azimuth) × 0.3m (range), and the scene was set to 5km × 5km. The scene and dot matrix settings are as follows: Figure 4 As shown, points A, B, C, D, and E were selected for imaging quality assessment. The satellite orbit is a lunar orbit, and its orbital parameters are shown in Table 1. Table 1. Satellite Orbit Parameters

[0077] The radar operating parameters of lunar orbiting satellite SAR are shown in Table 2: Table 2. Radar Operating Parameters

[0078] Satellite velocity error situation as follows Figure 5 As shown, the horizontal axis represents azimuth time, and the vertical axis represents satellite velocity, where curve 51 represents the error velocity and curve 52 represents the ideal velocity; the three-dimensional position error is as follows. Figure 6 As shown, curve 61 represents the error position, and curve 62 represents the ideal position. Figure 5 and Figure 6 It can be seen that there are large measurement errors in both satellite velocity information and three-dimensional position information. For points A, B, C, D and E, the two-dimensional contour maps of each point without parameter estimation are shown in Figure 7(a), Figure 7(b), Figure 7(c), Figure 7(d) and Figure 7(e) respectively. Due to the error in imaging parameters, all points are obviously out of focus.

[0079] For points A, B, C, D, and E, the two-dimensional contour maps of the final imaging results obtained by parameter estimation using the scheme of this embodiment are shown in Figures 8(a), 8(b), 8(c), 8(d), and 8(e), respectively. The quality assessment of the final imaging results is shown in Table 3. Table 3. Imaging Quality Assessment

[0080] In implementation, Taylor windowing operations of -25dB and -23dB were performed in the azimuth and range directions, respectively. As can be seen from Table 3, the resolution of all point targets met the design requirements. Furthermore, as can be seen from Figures 8(a), 8(b), 8(c), 8(d), and 8(e), the center point and the azimuth edge point achieved good focusing effect, proving the effectiveness of the scheme in this embodiment.

[0081] This embodiment utilizes a polynomial slant range model to analyze the relationship between NCS parameters and the azimuth spatial variation rate of the Doppler modulation frequency. It uses the maximum contrast method to estimate the Doppler modulation frequency and the least squares method to estimate the azimuth spatial variation rate of the Doppler modulation frequency, thereby achieving accurate estimation of NCS parameters and effectively improving the focusing effect of the final imaging result.

[0082] Corresponding to the embodiments of the aforementioned methods, this application also provides embodiments of a spaceborne SAR imaging device and a terminal for its application: like Figure 9 As shown, Figure 9 This is a block diagram of a spaceborne SAR imaging device provided in an embodiment of this application. The device includes: Processing module 91 is used to process the echo signal of the spaceborne SAR to obtain a preliminary focused image; The solution module 92 is used to select multiple sub-regions in the preliminary focused image, estimate the Doppler modulation frequency of each sub-region, and solve the azimuth spatial variation rate of the Doppler modulation frequency using the least squares method based on the estimation results. The correction module 93 is used to calculate the NCS parameters based on the azimuth spatial variation rate, and to perform spatial variation correction and imaging processing on the echo signal based on the NCS parameters to obtain the target image.

[0083] The specific implementation process of the functions and roles of each module in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0084] This application also provides an electronic device, please refer to [link to application]. Figure 10 , Figure 10 This is a structural block diagram of an electronic device provided in an embodiment of this application. The electronic device may include a processor 1010, a communication interface 1020, a memory 1030, and at least one communication bus 1040. The communication bus 1040 is used to enable direct communication between these components. In this embodiment, the communication interface 1020 of the electronic device is used for signaling or data communication with other node devices. The processor 1010 may be an integrated circuit chip with signal processing capabilities.

[0085] The processor 1010 described above can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor, or the processor 1010 can be any conventional processor.

[0086] The memory 1030 may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc. The memory 1030 stores computer-readable instructions. When these computer-readable instructions are executed by the processor 1010, the electronic device can perform the aforementioned operations. Figure 1 The various steps involved in the method implementation examples.

[0087] Alternatively, the electronic device may also include a storage controller and an input / output unit.

[0088] The memory 1030, storage controller, processor 1010, peripheral interface, and input / output unit are electrically connected directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses 1040. The processor 1010 is used to execute executable modules stored in the memory 1030, such as software function modules or computer programs included in electronic devices.

[0089] The input / output unit is used to provide users with the ability to create tasks and to set optional start periods or preset execution times for those tasks, thereby enabling user-server interaction. The input / output unit may be, but is not limited to, a mouse and keyboard.

[0090] Understandable. Figure 10 The structure shown is for illustrative purposes only; the electronic device may also include components that are more advanced than those shown. Figure 10The more or fewer components shown, or having the same Figure 10 The different configurations shown. Figure 10 The components shown can be implemented using hardware, software, or a combination thereof.

[0091] This application also provides a storage medium storing instructions. When the instructions are run on a computer, the computer program is executed by a processor to implement the method described in the method embodiment. To avoid repetition, the method will not be described again here.

[0092] 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.

[0093] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0094] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0095] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0096] 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.

[0097] 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 the claims.

[0098] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A spaceborne SAR imaging method, characterized in that, include: The echo signal from the spaceborne SAR is processed to obtain a preliminary focused image; Multiple sub-regions are selected in the preliminary focused image, the Doppler modulation frequency of each sub-region is estimated, and based on the estimation results, the azimuth spatial variation rate of the Doppler modulation frequency is solved using the least squares method. Based on the azimuth spatial variation rate, the NCS parameters are calculated, and the echo signal is subjected to spatial variation correction and imaging processing based on the NCS parameters to obtain the target image.

2. The method according to claim 1, characterized in that, Before processing the echo signal from the spaceborne SAR, the following steps are included: Establish the polynomial slant range model of the aforementioned spaceborne SAR; Based on the polynomial slant range model, the relationship between the NCS parameters and the azimuth spatial variation of the second expansion term of the slant range history of the spaceborne SAR is obtained.

3. The method according to claim 2, characterized in that, The polynomial slant distance model is expressed by the following formula: in, For a zero Doppler time is The corresponding slope distance is The slant distance history corresponding to the point target; Location and time; and These are the polynomial coefficients; The polynomial coefficients are expressed by the following formula: in, For polynomial coefficients, ; For reference target The first slant range history One expansion item; For the first The distance spatial variation of each expanded term; For the first The azimuth variation part of each expanded item.

4. The method according to claim 3, characterized in that, The relationship between the NCS parameters and the azimuth spatial variation of the second expansion term of the slant range history of the spaceborne SAR is expressed by the following formula: In the formula, The NCS parameters; The radar wavelength of the spaceborne SAR; The azimuth spatial variation is the second expansion term of the slant range history of the spaceborne SAR.

5. The method according to claim 1, characterized in that, The step of selecting multiple sub-regions in the preliminary focused image includes: Multiple candidate regions are divided in the preliminary focused image using a two-dimensional sliding window; Calculate the contrast of each candidate region, and select several sub-regions from the multiple candidate regions based on the contrast.

6. The method according to claim 1, characterized in that, The estimation of the Doppler modulation frequency of each sub-region includes: Using the maximum contrast method, Doppler frequency modulation estimation is performed on each selected sub-region to obtain the corresponding Doppler frequency modulation estimate value.

7. The method according to claim 6, characterized in that, The step of solving the azimuth spatial variation rate of the Doppler modulation frequency using the least squares method based on the estimation results includes: Based on the Doppler modulation frequency estimates of multiple sub-regions, the polynomial coefficients of the multiple sub-regions are obtained; An objective function is constructed based on the polynomial coefficients of the multiple sub-regions; the objective function represents the functional relationship between the polynomial coefficients and the azimuth spatial variation rate and range spatial variation rate of the Doppler modulation frequency; The objective function is converted into a matrix equation, and the least squares method is used to solve the matrix equation to obtain the azimuth spatial variation rate of the Doppler modulation frequency.

8. The method according to claim 7, characterized in that, The matrix equation is expressed as: in, for The vector form of ; For the first Polynomial coefficients of each subregion , The total number of the multiple sub-regions; For the first The zero Doppler time corresponding to the Doppler modulation frequency estimate of each sub-region The slant range corresponding to the zero Doppler time; The azimuth spatial variation rate of the Doppler modulation frequency; The distance spatial variation rate is the frequency of the Doppler modulation.

9. The method according to claim 2, characterized in that, The NCS parameters are calculated based on the following formula: In the formula, The azimuth spatial variation rate of the Doppler modulation frequency.

10. A spaceborne SAR imaging device, characterized in that, include: The processing module is used to process the echo signals of the spaceborne SAR to obtain a preliminary focused image; The solution module is used to select multiple sub-regions in the preliminary focused image, estimate the Doppler modulation frequency of each sub-region, and use the least squares method to solve the azimuth spatial variation rate of the Doppler modulation frequency based on the estimation results. The correction module is used to calculate the NCS parameters based on the azimuth spatial variation rate, and to perform spatial variation correction and imaging processing on the echo signal based on the NCS parameters to obtain the target image.

11. A computer-readable storage medium, characterized in that, It stores a computer program thereon, which, when executed by a processor, implements the method as described in any one of claims 1 to 9.

12. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as claimed in any one of claims 1 to 9.

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