Parameter Correction Method and Device for Airborne InSAR 3D Reconstruction

Abstract

This invention discloses a parameter correction method and apparatus for airborne InSAR 3D reconstruction, belonging to the field of synthetic aperture radar interferometry technology. The method includes the following steps: S1, acquiring an interferometric unwrapped phase map, interferometric imaging parameters, a phase unwrapped quality map, and control point data; S2, filtering control point data based on the phase unwrapped quality map, and removing control points with poor unwrapped quality; S3, establishing a parameter correction model based on the remaining control points and the interferometric 3D reconstruction model, and solving for the corrected 3D reconstruction parameters using an adaptive iterative adjustment method with normal equation coefficient matrix optimization; S4, performing orientation iteration of the interferometric 3D reconstruction model using the corrected 3D reconstruction parameters, and removing gross error control points based on the control point orientation error; S5, repeating steps S3 and S4 until the control point orientation error tends to stabilize, obtaining the final corrected parameters. This invention achieves accurate correction of airborne InSAR 3D reconstruction parameters.

Description

Technical Field

[0001] This invention relates to a parameter correction method and apparatus for airborne InSAR three-dimensional reconstruction, belonging to the field of synthetic aperture radar interferometry technology. Background Technology

[0002] Synthetic Aperture Radar (SAR), as an active imaging sensor, can overcome the limitations of natural conditions such as lighting and weather, enabling all-day, all-weather Earth observation. It is widely used in many fields, including topographic mapping, natural resource surveys and monitoring, disaster emergency response, and military reconnaissance. InSAR (Interferometric SAR) technology is an extension of SAR technology. Utilizing the mathematical relationship between interferometric phase and terrain elevation, it has become an important remote sensing technique for measuring three-dimensional information of the Earth's surface (especially surface deformation). Achieving high-precision InSAR three-dimensional terrain inversion requires high-precision system parameters. However, in the actual imaging process of InSAR systems, errors inevitably exist in the system parameters. These errors can further lead to deviations in terrain inversion, therefore parameter correction is necessary.

[0003] Parameters affecting InSAR 3D reconstruction can be categorized into two types: geometric parameters and interferometric parameters. Geometric positioning parameters mainly include sensor position, slant range, azimuth imaging time, and Doppler frequency; interferometric parameters mainly include interferometric baseline and interferometric phase. Since processing geometric and interferometric parameters requires scientifically sound models, and the two types of parameters are coupled, simultaneous optimization is challenging. Currently, many control-point-based interferometric system parameter correction methods employ a step-by-step correction strategy: first, geometric parameters are corrected based on the geometric positioning model, and then interferometric parameters are corrected based on the interferometric equations. However, step-by-step processing leads to residual parameter errors, thus affecting the accuracy of interferometric 3D reconstruction. Therefore, integrated correction of geometric and interferometric parameters is a more ideal solution.

[0004] Integrated calibration of geometric and interferometric parameters helps improve the accuracy of interferometric 3D reconstruction. This integrated calibration requires a parameter calibration model constructed based on control points and a suitable interferometric 3D reconstruction model, followed by adjustment calculations to achieve accurate parameter calibration. Due to the coupling correlation between the two types of parameters, the optimized adjustment calculation of the calibration model is particularly crucial. Simultaneously, the quality of the control points also affects the accuracy of parameter calibration, thus impacting the interferometric 3D inversion results. Therefore, control points containing gross errors must be removed to achieve high-precision parameter calibration. Summary of the Invention

[0005] To address the aforementioned issues, this invention proposes a parameter correction method and apparatus for airborne InSAR 3D reconstruction, which can accurately correct interferometric 3D reconstruction parameters using control points.

[0006] The technical solution adopted by this invention to solve its technical problem is as follows:

[0007] In a first aspect, an embodiment of the present invention provides a parameter correction method for airborne InSAR three-dimensional reconstruction, comprising the following steps:

[0008] Step S1: Obtain the interferometric unwrapping phase map, interferometric imaging parameters, phase unwrapping quality map, and control point data;

[0009] Step S2: Based on the phase unwrapping quality map, filter the control point data and remove control points with poor unwrapping quality;

[0010] Step S3: Based on the remaining control points and the interferometric 3D reconstruction model, establish a parameter correction model, and use the adaptive iterative adjustment solution method of normal equation coefficient matrix optimization to obtain the corrected 3D reconstruction parameters.

[0011] Step S4: Use the corrected 3D reconstruction parameters to perform directional iteration of the interferometric 3D reconstruction model, and remove gross control points based on the control point orientation error;

[0012] Step S5: Repeat steps S3 and S4 until the control point orientation error tends to stabilize, and obtain the final correction parameters.

[0013] As one possible implementation of this embodiment, the removal of control points with poor unwrapping quality includes the following steps:

[0014] Obtain the image coordinates of each control point, and extract the corresponding phase unwrapping quality coefficient from the phase unwrapping quality map based on the image coordinates;

[0015] If the quality coefficient is less than a preset threshold, the control point is removed. The preset threshold is 0.6-0.8.

[0016] As one possible implementation of this embodiment, the interferometric three-dimensional reconstruction model is as follows:

[0017] ,

[0018] in, The coordinates of the phase center of the main image antenna in the geocentric rectangular coordinate system. ground target point P Coordinates in a geocentric rectangular coordinate system The slant range corresponding to the main image antenna. This is the transformation matrix from VNW coordinates to geocentric rectangular coordinates. The unit view vector in VNW coordinates; Calculated from interferometric 3D reconstruction parameters:

[0019] ,

[0020] in, For radar wavelength, For Doppler frequency, For interference phase, Baseline length The baseline component length in the sensor velocity direction. The component of the baseline perpendicular to the velocity direction. Antenna mode, This indicates the "single send, double receive" mode. It indicates the "ping-pong" mode.

[0021] As one possible implementation of this embodiment, the establishment of the parameter correction model includes:

[0022] Establish the observation equations for the parameter correction model:

[0023] ,

[0024] With initial distance Distance resolution Initial imaging time in azimuth direction Azimuth imaging time interval Interference baseline length Interference baseline tilt angle Interference phase bias As adjustment parameters, establish the parameter correction error equation:

[0025] ,

[0026] For each control point, a set of error equations is formulated. These error equations are then combined to form a system of error equations, which is written in matrix form.

[0027] ,

[0028] If there are n control points, where These are the corrections to the adjustment parameters.

[0029] , , The superscript represents the control point number;

[0030] Based on the least squares principle, the adjustment method equations are established as follows:

[0031] ,

[0032] in , .

[0033] As one possible implementation of this embodiment, the method of obtaining the corrected 3D reconstruction parameters by optimizing the coefficient matrix of the normal equations includes:

[0034] Set optimization coefficients For the coefficient matrix of the adjustment method equation Optimize:

[0035] ,

[0036] in, For matrix The diagonal elements;

[0037] Using the optimized coefficient matrix Solve for the corrections to the adjustment parameters Using corrections to reconstruct interferometric parameters Corrections are made, and the corrected interferometric reconstruction parameters are obtained. Substitute the corrected interferometric reconstruction parameters into the adjustment observation equation to calculate the residual vector. Then calculate the adjustment residuals. ;

[0038] The error equation is re-established using the corrected interferometric reconstruction parameters, and the adjustment residuals are used as a basis. Changes in optimization coefficients Perform adaptive correction if If the value decreases, the optimized parameters are corrected. ;if If the value increases, the corrected optimization parameters will be... ;

[0039] This adjustment process is repeated iteratively until the residual value is reached. The change is less than the threshold The adjusted interferometric 3D reconstruction parameters are obtained.

[0040] As one possible implementation of this embodiment, the step of using the corrected 3D reconstruction parameters to perform directional iteration of the interferometric 3D reconstruction model and removing gross control points based on the control point orientation error includes:

[0041] For each control point, the image coordinates and the corresponding untangling phase Substituting the data into the interferometric 3D reconstruction model, the geographic coordinates are obtained. and the known geographic coordinates of the control points Perform orientation comparisons and calculate the interferometric orientation errors of the control points. Statistically analyze the interferometric orientation errors of all control points and calculate the standard error of the interferometric orientation. ,in, For the first i Interference orientation error at each control point;

[0042] Compare the control point interferometric orientation error with the mean error of interferometric orientation, such as If the control point is not found to be gross, it is considered a gross error and is removed.

[0043] As one possible implementation of this embodiment, repeating steps S3 and S4 until the control point orientation error tends to stabilize and the final correction parameters are obtained includes:

[0044] The remaining control points are then subjected to orientation calculations. The mean square error of the interferometric orientation is calculated and gross errors are eliminated. This process of iterative orientation is repeated until the mean square error of the interferometric orientation remains constant.

[0045] Secondly, an embodiment of the present invention provides a parameter correction device for airborne InSAR three-dimensional reconstruction, comprising:

[0046] The data acquisition module is used to acquire interferometric unwrapped phase maps, interferometric imaging parameters, phase unwrapped quality maps, and control point data.

[0047] The control point filtering module is used to filter control point data based on the phase unwrapping quality map and remove control points with poor unwrapping quality.

[0048] The parameter correction module is used to establish a parameter correction model based on the remaining control points and the interferometric 3D reconstruction model, and to solve for the corrected 3D reconstruction parameters using an adaptive iterative adjustment solution method that optimizes the coefficient matrix of the normal equations.

[0049] The gross error removal module is used to perform directional iteration of the interferometric 3D reconstruction model using the corrected 3D reconstruction parameters, and to remove gross control points based on the control point orientation error.

[0050] The iterative optimization module is used for repeated parameter correction and gross error elimination until the control point orientation error tends to stabilize, thus obtaining the final correction parameters.

[0051] Thirdly, an electronic device provided by an embodiment of the present invention includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus, and the processor executes the machine-readable instructions to perform the steps of the parameter correction method for arbitrary airborne InSAR three-dimensional reconstruction as described above.

[0052] Fourthly, embodiments of the present invention provide a storage medium storing a computer program, which, when run by a processor, executes the steps of the parameter correction method for arbitrary airborne InSAR three-dimensional reconstruction as described above.

[0053] The beneficial effects of the technical solutions in the embodiments of the present invention are as follows:

[0054] This invention first acquires interferometric unwrapped phase maps, interferometric imaging parameters, phase unwrapped quality maps, and control point data. The phase unwrapped quality maps are used to filter the control point data, eliminating control points with poor unwrapped quality. Then, for the interferometric 3D reconstruction parameters, a parameter correction model is established based on the interferometric 3D reconstruction model using the control points. The parameter correction model equations are solved using an adaptive iterative adjustment method with a normal equation coefficient matrix optimization, yielding the corrected 3D reconstruction parameters. The corrected 3D reconstruction parameters are then used for the orientation iteration of the interferometric 3D reconstruction model. Gross error control points are eliminated based on the control point orientation error. The remaining control points are then used for parameter correction, and this process of iterative correction continues until the control point orientation error no longer changes, resulting in the final corrected interferometric 3D reconstruction parameters. This achieves accurate correction of airborne InSAR 3D reconstruction parameters.

[0055] This invention effectively improves the parameter accuracy of airborne InSAR 3D reconstruction through integrated parameter correction, control point quality optimization, and adaptive solution, making it suitable for high-precision applications such as topographic mapping and disaster monitoring. During SAR image data interferometric processing, this invention optimizes control points using phase unwrapping quality coefficients and directional iteration of the interferometric 3D reconstruction model. It also employs an adaptive iterative adjustment solution method based on the normal equation coefficient matrix optimization to effectively overcome coupling-related problems in the integrated parameter correction process for interferometric 3D reconstruction. Compared with existing technologies, this invention offers superior technical performance. Attached Figure Description

[0056] Figure 1 This is a flowchart illustrating a parameter correction method for airborne InSAR three-dimensional reconstruction according to an exemplary embodiment;

[0057] Figure 2 This is a schematic diagram of the structure of a parameter correction device for airborne InSAR three-dimensional reconstruction according to an exemplary embodiment. Detailed Implementation

[0058] To more clearly illustrate the technical features of the present invention, the present invention will be described in detail below through specific embodiments and in conjunction with the accompanying drawings.

[0059] like Figure 1As shown in the figure, an embodiment of the present invention provides a parameter correction method for airborne InSAR three-dimensional reconstruction, which includes the following steps:

[0060] Step S1: Obtain the interferometric unwrapping phase map, interferometric imaging parameters, phase unwrapping quality map, and control point data;

[0061] Step S2: Based on the phase unwrapping quality map, filter the control point data and remove control points with poor unwrapping quality;

[0062] Step S3: Based on the remaining control points and the interferometric 3D reconstruction model, establish a parameter correction model, and use the adaptive iterative adjustment solution method of normal equation coefficient matrix optimization to obtain the corrected 3D reconstruction parameters.

[0063] Step S4: Use the corrected 3D reconstruction parameters to perform directional iteration of the interferometric 3D reconstruction model, and remove gross control points based on the control point orientation error;

[0064] Step S5: Repeat steps S3 and S4 until the control point orientation error tends to stabilize, and obtain the final correction parameters.

[0065] As one possible implementation of this embodiment, the removal of control points with poor unwrapping quality includes the following steps:

[0066] Obtain the image coordinates of each control point, and extract the corresponding phase unwrapping quality coefficient from the phase unwrapping quality map based on the image coordinates;

[0067] If the quality coefficient is less than a preset threshold, the control point is removed. The preset threshold is 0.6-0.8. This threshold range has been verified in practice. Within this range, control points with poor unwrapping quality can be effectively identified, balancing the influence of the number and quality of control points on the correction results.

[0068] As one possible implementation of this embodiment, the interferometric three-dimensional reconstruction model is as follows:

[0069] ,

[0070] in, The coordinates of the phase center of the main image antenna in the geocentric rectangular coordinate system. ground target point P Coordinates in a geocentric rectangular coordinate system The slant range corresponding to the main image antenna. This is the transformation matrix from VNW coordinates to geocentric rectangular coordinates. The unit view vector in VNW coordinates; Calculated from interferometric 3D reconstruction parameters:

[0071] ,

[0072] in, For radar wavelength, For Doppler frequency, For interference phase, Baseline length The baseline component length in the sensor velocity direction. The component of the baseline perpendicular to the velocity direction. Antenna mode, This indicates the "single send, double receive" mode. It indicates the "ping-pong" mode.

[0073] As one possible implementation of this embodiment, the establishment of the parameter correction model includes:

[0074] Establish the observation equations for the parameter correction model:

[0075] ,

[0076] With initial distance Distance resolution Initial imaging time in azimuth direction Azimuth imaging time interval Interference baseline length Interference baseline tilt angle Interference phase bias As adjustment parameters, establish the parameter correction error equation:

[0077] ,

[0078] For each control point, a set of error equations is formulated. These error equations are then combined to form a system of error equations, which is written in matrix form.

[0079] ,

[0080] If there are n control points, where These are the corrections to the adjustment parameters.

[0081] , , The superscript represents the control point number;

[0082] Based on the least squares principle, the adjustment method equations are established as follows:

[0083] ,

[0084] in , .

[0085] As one possible implementation of this embodiment, the method of obtaining the corrected 3D reconstruction parameters by optimizing the coefficient matrix of the normal equations includes:

[0086] Set optimization coefficients For the coefficient matrix of the adjustment method equation Optimize:

[0087] ,

[0088] in, For matrix The diagonal elements;

[0089] Using the optimized coefficient matrix Solve for the corrections to the adjustment parameters Using corrections to reconstruct interferometric parameters Corrections are made, and the corrected interferometric reconstruction parameters are obtained. Substitute the corrected interferometric reconstruction parameters into the adjustment observation equation to calculate the residual vector. Then calculate the adjustment residuals. ;

[0090] The error equation is re-established using the corrected interferometric reconstruction parameters, and the adjustment residuals are used as a basis. Changes in optimization coefficients Perform adaptive correction if If the value decreases, the optimized parameters are corrected. ;if If the value increases, the corrected optimization parameters will be... ;

[0091] This adjustment process is repeated iteratively until the residual value is reached. The change is less than the threshold The adjusted interferometric 3D reconstruction parameters are obtained. Here, the threshold... The preferred value is 0.1m. Iterative operations are performed continuously until the change in residual modulus meets the set accuracy requirements, ensuring that the parameter correction achieves high accuracy and that the 3D reconstruction parameters meet the accuracy standards for practical applications.

[0092] As one possible implementation of this embodiment, the step of using the corrected 3D reconstruction parameters to perform directional iteration of the interferometric 3D reconstruction model and removing gross control points based on the control point orientation error includes:

[0093] For each control point, the image coordinates and the corresponding untangling phase Substituting the data into the interferometric 3D reconstruction model, the geographic coordinates are obtained. and the known geographic coordinates of the control points Perform orientation comparisons and calculate the interferometric orientation errors of the control points. Statistically analyze the interferometric orientation errors of all control points and calculate the standard error of the interferometric orientation. ,in, For the first i Interference orientation error at each control point;

[0094] Compare the control point interferometric orientation error with the mean error of interferometric orientation, such as If the control point is not found to be gross, it is considered a gross error and is removed.

[0095] As one possible implementation of this embodiment, repeating steps S3 and S4 until the control point orientation error tends to stabilize and the final correction parameters are obtained includes:

[0096] The remaining control points are then subjected to orientation calculations. The mean square error of the interferometric orientation is calculated and gross errors are eliminated. This process of iterative orientation is repeated until the mean square error of the interferometric orientation remains constant.

[0097] The directional error tending to stabilize means that the difference in the directional error between two consecutive iterations is less than 0.05m. This standard quantifies the degree of change in the directional error during the iteration process. When the difference in the directional error between two consecutive iterations is less than this threshold, the correction result is considered to have stabilized, that is, the interferometric directional error is considered to remain unchanged, and a high level of accuracy has been achieved. The final correction parameters can then be output for actual airborne InSAR 3D reconstruction.

[0098] like Figure 2 As shown in the figure, an embodiment of the present invention provides a parameter correction device for airborne InSAR three-dimensional reconstruction, comprising:

[0099] The data acquisition module is used to acquire interferometric unwrapped phase maps, interferometric imaging parameters, phase unwrapped quality maps, and control point data.

[0100] The control point filtering module is used to filter control point data based on the phase unwrapping quality map and remove control points with poor unwrapping quality.

[0101] The parameter correction module is used to establish a parameter correction model based on the remaining control points and the interferometric 3D reconstruction model, and to solve for the corrected 3D reconstruction parameters using an adaptive iterative adjustment solution method that optimizes the coefficient matrix of the normal equations.

[0102] The gross error removal module is used to perform directional iteration of the interferometric 3D reconstruction model using the corrected 3D reconstruction parameters, and to remove gross control points based on the control point orientation error.

[0103] The iterative optimization module is used for repeated parameter correction and gross error elimination until the control point orientation error tends to stabilize, thus obtaining the final correction parameters.

[0104] The specific process of using the technical solution of this invention to correct airborne InSAR three-dimensional reconstruction parameters is as follows.

[0105] Step 1: Acquisition of multi-source data.

[0106] Acquire interferometric unwrapped phase maps, interferometric imaging parameters, phase unwrapped quality maps, and control point data. This provides a comprehensive data foundation for subsequent calibration work. The interferometric unwrapped phase map contains surface phase information and is crucial data for 3D reconstruction; the interferometric imaging parameters determine the basic characteristics of the imaging; the phase unwrapped quality map is used to evaluate the reliability of phase unwrapping; and the control point data, as known and precise coordinate information, is used to calibrate other parameters.

[0107] Step 2: Initial screening of control points.

[0108] The control point data was filtered using the phase unwrapping quality map to remove control points with poor unwrapping quality, and the image coordinates of each control point were obtained. The phase unwrapping quality coefficient is obtained from the phase unwrapping quality map based on the image coordinates and compared with a set threshold. If the quality coefficient of a control point is less than the threshold, the control point is removed. This step removes control points that may introduce large errors due to poor phase unwrapping quality, improves the quality of control points participating in subsequent correction processes, and thus enhances the overall accuracy of the correction.

[0109] Step 3: Parameter calibration model construction and solution.

[0110] A parameter correction model is established based on the remaining control points and the interferometric 3D reconstruction model. An adaptive iterative adjustment solution method with optimization of the normal equation coefficient matrix is ​​used to solve for the corrected 3D reconstruction parameters.

[0111] Step 3 is implemented as follows:

[0112] Using an interferometric 3D reconstruction model:

[0113] ,

[0114] in, The coordinates of the phase center of the main image antenna in the geocentric rectangular coordinate system are as follows: ground target points P Coordinates in a geocentric rectangular coordinate system The slant range corresponding to the main image antenna. This is the transformation matrix from VNW coordinates to geocentric rectangular coordinates. The unit view vector in VNW coordinates; Calculated from the corresponding interferometric 3D reconstruction parameters:

[0115] ,

[0116] in, For radar wavelength, For Doppler frequency, For interference phase, Baseline length The baseline component length in the sensor velocity direction. The component of the baseline perpendicular to the velocity direction. Antenna mode, This indicates the "single send, double receive" mode. Indicates "Ping Pong" mode;

[0117] Establish the observation equations for the parameter correction model:

[0118] ,

[0119] With initial distance Distance resolution Initial imaging time in azimuth direction Azimuth imaging time interval Interference baseline length Interference baseline tilt angle Interference phase bias As adjustment parameters, establish the parameter correction error equation:

[0120] ,

[0121] For each control point, a set of error equations can be formulated. By combining the error equations of all control points, a system of error equations can be formed and written in matrix form:

[0122]

[0123] If there are n control points, where These are the corrections to the adjustment parameters.

[0124] , , The superscript represents the control point number;

[0125] Based on the least squares principle, the adjustment method equations are established as follows:

[0126] ,

[0127] in , ;

[0128] For the coefficient matrix of the adjustment method equation Optimize the matrix by setting optimization coefficients. The optimized coefficient matrix:

[0129] ,

[0130] For matrix The diagonal elements. Using the optimized coefficient matrix. Solve for the corrections to the adjustment parameters Using corrections to reconstruct interferometric parameters Corrections are made, and the corrected interferometric reconstruction parameters are obtained. Substitute the corrected interferometric reconstruction parameters into the adjustment observation equation to calculate the residual vector. Then calculate the adjustment residuals. ;

[0131] The error equation is re-established using the corrected interferometric reconstruction parameters, and the adjustment residuals are used as a basis. Changes in optimization coefficients Perform adaptive correction if If the value decreases, the optimized parameters are corrected. ;if If the value decreases, the optimized parameters are corrected. ;

[0132] This adjustment process is repeated iteratively until the residual value is reached. The change is less than the threshold The interferometric reconstruction parameters after adjustment are obtained.

[0133] The model constructed in step 3 comprehensively considers the relationship between various parameters. Through the optimized iterative adjustment solution method, it can more accurately solve the 3D reconstruction parameters that are affected by various factors and have deviations, and achieve preliminary correction of the parameters.

[0134] Step 4: Remove gross error control points.

[0135] The corrected 3D reconstruction parameters are used to perform model orientation iteration, and gross control points are eliminated based on the control point orientation error.

[0136] The specific implementation process of step 4 is as follows:

[0137] For each control point, the image coordinates and the corresponding untangling phase Substituting the data into the interferometric 3D reconstruction model, the geographic coordinates are obtained. and the known geographic coordinates of the control points Perform orientation comparisons and calculate the interferometric orientation errors of the control points. Statistically analyze the interferometric orientation errors of all control points and calculate the standard error of the interferometric orientation. ;

[0138] Compare the control point interferometric orientation error and the mean square error, such as If the control point is not found to be gross, it is considered a gross error and is removed.

[0139] The remaining control points are then subjected to orientation calculations. The mean square error of the interferometric orientation is calculated and gross errors are eliminated. This process is repeated iteratively until the mean square error of the interferometric orientation remains constant.

[0140] Step 4 involves actual model orientation iteration to identify and remove gross control points that do not conform to the overall correction trend and cause large orientation errors, thereby further purifying the data used for parameter correction and improving the stability and reliability of the correction results.

[0141] Step 5: Iterative optimization.

[0142] Steps 3 and 4 are repeated using the remaining control points after removing outlier control points to iteratively correct the interferometric 3D reconstruction parameters until the control point interferometric orientation error no longer changes, thus obtaining the final corrected interferometric 3D reconstruction parameters. Through continuous iteration, the parameter correction model is gradually optimized to make the correction results more accurate until the control point orientation error reaches a stable state, ensuring that the final corrected parameters best reflect the actual situation are obtained, thereby improving the accuracy of airborne InSAR 3D reconstruction.

[0143] Compared with the prior art, the present invention has the following characteristics:

[0144] 1. Integrated parameter calibration: By establishing a parameter calibration model, geometric parameters and interference parameters are optimized simultaneously, thus solving the parameter coupling error problem caused by step calibration;

[0145] 2. Control point quality optimization: By combining phase unwrapping quality map and orientation error for dual screening, low-quality and gross error control points are eliminated to improve correction stability;

[0146] 3. Adaptive solution mechanism: The iterative adjustment method of optimizing the coefficient matrix of the normal equation is adopted to dynamically adjust the solution parameters, thereby improving the correction accuracy and convergence speed.

[0147] An electronic device provided by an embodiment of the present invention includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus, and the processor executes the machine-readable instructions to perform the steps of the parameter correction method for arbitrary airborne InSAR three-dimensional reconstruction as described above.

[0148] Specifically, the aforementioned memory and processor can be general-purpose memory and processor, without any specific limitations. When the processor runs the computer program stored in the memory, it can execute the aforementioned parameter correction method for airborne InSAR three-dimensional reconstruction.

[0149] Corresponding to the above application startup method, this embodiment of the invention also provides a storage medium storing a computer program, which, when run by a processor, performs the steps of the parameter correction method for arbitrary airborne InSAR three-dimensional reconstruction as described above.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A parameter correction method for airborne InSAR three-dimensional reconstruction, characterized in that, Includes the following steps: Step S1: Obtain the interferometric unwrapping phase map, interferometric imaging parameters, phase unwrapping quality map, and control point data; Step S2: Based on the phase unwrapping quality map, filter the control point data and remove control points with poor unwrapping quality; Step S3: Based on the remaining control points and the interferometric 3D reconstruction model, establish a parameter correction model, and use the adaptive iterative adjustment solution method of normal equation coefficient matrix optimization to obtain the corrected 3D reconstruction parameters. Step S4: Use the corrected 3D reconstruction parameters to perform directional iteration of the interferometric 3D reconstruction model, and remove gross control points based on the control point orientation error; Step S5: Repeat steps S3 and S4 until the control point orientation error tends to stabilize, and obtain the final correction parameters.

2. The parameter correction method for airborne InSAR three-dimensional reconstruction according to claim 1, characterized in that, The process of removing control points with poor unwrapping quality includes the following steps: Obtain the image coordinates of each control point, and extract the corresponding phase unwrapping quality coefficient from the phase unwrapping quality map based on the image coordinates; If the quality coefficient is less than a preset threshold, the control point is removed. The preset threshold is 0.6-0.

8.

3. The parameter correction method for airborne InSAR three-dimensional reconstruction according to claim 1 or 2, characterized in that, The interferometric three-dimensional reconstruction model is as follows: ， in, The coordinates of the phase center of the main image antenna in the geocentric rectangular coordinate system. ground target point P Coordinates in a geocentric rectangular coordinate system The slant range corresponding to the main image antenna. This is the transformation matrix from VNW coordinates to geocentric rectangular coordinates. The unit view vector in VNW coordinates; Calculated from interferometric 3D reconstruction parameters: ， in, For radar wavelength, For Doppler frequency, For interference phase, Baseline length The baseline component length in the sensor velocity direction. The component of the baseline perpendicular to the velocity direction. Antenna mode, This indicates the "single send, double receive" mode. It indicates the "Ping Pong" mode.

4. The parameter correction method for airborne InSAR three-dimensional reconstruction according to claim 3, characterized in that, The establishment of the parameter correction model includes: Establish the observation equations for the parameter correction model: ， With initial distance Distance resolution Initial imaging time in azimuth direction Azimuth imaging time interval Interference baseline length Interference baseline tilt angle Interference phase bias As adjustment parameters, establish the parameter correction error equation: ， For each control point, a set of error equations is formulated. These error equations are then combined to form a system of error equations, which is written in matrix form. ， If there are n control points, where These are the corrections to the adjustment parameters. , , The superscript represents the control point number; Based on the least squares principle, the adjustment method equations are established as follows: ， in , .

5. The parameter correction method for airborne InSAR three-dimensional reconstruction according to claim 4, characterized in that, The adaptive iterative adjustment solution method using the normal equation coefficient matrix optimization is used to obtain the corrected 3D reconstruction parameters, including: Set optimization coefficients For the coefficient matrix of the adjustment method equation Optimize: ， in, For matrix The diagonal elements; Using the optimized coefficient matrix Solve for the corrections to the adjustment parameters Using corrections to reconstruct interferometric parameters Corrections are made, and the corrected interferometric reconstruction parameters are obtained. Substitute the corrected interferometric reconstruction parameters into the adjustment observation equation to calculate the residual vector. Then calculate the adjustment residuals. ; The error equation is re-established using the corrected interferometric reconstruction parameters, and the adjustment residuals are used as a basis. Changes in optimization coefficients Perform adaptive correction, if If the value decreases, the corrected optimization parameters will be... ;if If the value increases, the optimized parameters will be corrected. ; This adjustment process is repeated iteratively until the residual value is reached. The change is less than the threshold The adjusted interferometric 3D reconstruction parameters are obtained.

6. The parameter correction method for airborne InSAR three-dimensional reconstruction according to claim 5, characterized in that, The step of using the corrected 3D reconstruction parameters to perform directional iteration of the interferometric 3D reconstruction model, and removing gross control points based on the control point orientation error, includes: For each control point, the image coordinates and the corresponding untangling phase Substituting the data into the interferometric 3D reconstruction model, the geographic coordinates are obtained. and the known geographic coordinates of the control points Perform orientation comparisons and calculate the interferometric orientation errors of the control points. Statistically analyze the interferometric orientation errors of all control points and calculate the standard error of the interferometric orientation. ,in, For the first i Interference orientation error at each control point; Compare the control point interferometric orientation error with the mean error of interferometric orientation, such as If the control point is not found to be gross, it is considered a gross error and is removed.

7. The parameter correction method for airborne InSAR three-dimensional reconstruction according to claim 6, characterized in that, Repeat steps S3 and S4 until the control point orientation error tends to stabilize, obtaining the final correction parameters, including: The remaining control points are then subjected to orientation calculations. The mean square error of the interferometric orientation is calculated and gross errors are eliminated. This process of iterative orientation is repeated until the mean square error of the interferometric orientation remains constant.

8. A parameter correction device for airborne InSAR three-dimensional reconstruction, characterized in that, include: The data acquisition module is used to acquire interferometric unwrapped phase maps, interferometric imaging parameters, phase unwrapped quality maps, and control point data. The control point filtering module is used to filter control point data based on the phase unwrapping quality map and remove control points with poor unwrapping quality. The parameter correction module is used to establish a parameter correction model based on the remaining control points and the interferometric 3D reconstruction model, and to solve for the corrected 3D reconstruction parameters using an adaptive iterative adjustment solution method that optimizes the coefficient matrix of the normal equations. The gross error removal module is used to perform directional iteration of the interferometric 3D reconstruction model using the corrected 3D reconstruction parameters, and to remove gross control points based on the control point orientation error. The iterative optimization module is used for repeated parameter correction and gross error elimination until the control point orientation error tends to stabilize, thus obtaining the final correction parameters.

9. An electronic device, characterized in that, The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions that the processor can execute. When the electronic device is running, the processor communicates with the memory via the bus, and the processor executes the machine-readable instructions to perform the steps of the parameter correction method for airborne InSAR three-dimensional reconstruction as described in any one of claims 1-7.

10. A storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, performs the steps of the parameter correction method for airborne InSAR three-dimensional reconstruction as described in any one of claims 1-7.

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