Method, device and equipment for generating digital surface model taking into account both plane and elevation

Abstract

The present invention provides a method, device and equipment for generating a digital surface model that takes both plane and elevation into consideration, including: determining geometric correction parameters corresponding to an InSAR interferometer pair, and determining an initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase; extracting elevation correction control points from the InSAR interferometer pair based on reference DEM data, optical reference datum and geometric correction parameters, and performing fine processing on the initial baseline to obtain a target baseline; performing phase-to-height conversion processing on the unwrapped phase based on the geometric correction parameters and the target baseline to obtain a target digital surface model. The present invention effectively solves the problem of incorrect plane position of the digital surface model extracted by InSAR and inconsistent elevation values ​​in overlapping areas when there are no ground control points and it is difficult to obtain accurate InSAR orbital state vector information, and realizes the joint application of digital surface models extracted by InSAR in large areas.

Description

Technical Field

[0001] The present invention relates to the field of satellite technology, and in particular to a method, device and equipment for generating a digital surface model taking both plane and elevation into consideration. Background Art

[0002] Interferometric Synthetic Aperture Radar (InSAR) is a radar technology used in surveying and remote sensing. Based on InSAR technology, a digital surface model (DSM) can be quickly obtained. The DSM production process for independent interferometric pairs mainly includes the following steps: primary and secondary image registration, interferometric pattern generation, removal of flat ground effects, interferometric pattern filtering, phase unwrapping, baseline estimation, and phase height conversion. In view of the need to produce DSM for large-area, multi-strip InSAR data, the existing DSM results extracted by InSAR processing based on independent interferometric pairs have problems such as plane position errors and inconsistent elevation values ​​in overlapping areas, and cannot be used in combination.

[0003] Related technology: "A method for InSAR interferometric parameter block adjustment using Schreiber's rule" (application number: CN201510480882.0), relates to a method for InSAR interferometric parameter block adjustment using Schreiber's rule, firstly obtaining an appropriate number of elevation control points and the unwrapping results of each interferogram within the image coverage range; taking each interferometric image pair as the basic adjustment unit, using a certain number of elevation control points and the same-name connection points at the overlap of different image pairs, and listing the error equation according to the InSAR interferometric parameter calibration principle; using Schreiber's rule, constructing an equivalent error equation for the connection point error equation, using the equivalent error equation for adjustment processing, and solving the interference parameters such as the baseline parameters and the interference phase offset of each interferometric image pair. The above method uses the Schreiber's rule to construct an equivalent error equation for the connection point error equation, and uses the equivalent error equation to solve the InSAR interferometric parameter block adjustment, which can effectively reduce the size of the error equation and the normal equation coefficient matrix, which not only reduces the requirements for computer configuration, but also improves the efficiency of the adjustment solution.

[0004] Related technology: "Regional block adjustment method for initial DSM for InSAR" (application number: CN202110783009.4), discloses a regional block adjustment method for initial DSM for InSAR, the method comprising the following steps: step S1, generating an initial DSM and additional data; step S2, calculating the pixel coordinates of the control points in the main image; step S3, determining the adjacency matrix of each initial DSM; step S4, uniformly extracting the connection points at the overlap of each initial DSM, and calculating the pixel coordinates of the connection points in the initial DSM and the pixel coordinates in the image adjacent to the initial DSM; step S5, determining the elevation value of the connection point after phase-elevation conversion; step S6, constructing the least squares adjustment equation, and performing regional block adjustment on the initial DSM. This invention can support the further improvement of the accuracy of the initial DSM products produced in a process-based manner during commercial InSAR topographic mapping.

[0005] The above InSAR DSM extraction adjustment methods all require the use of ground control points. For areas lacking high-precision three-dimensional coordinates and ground control, it is impossible to obtain InSAR DSM results with joint correction of plane position and elevation. Summary of the invention

[0006] In view of this, the purpose of the present invention is to provide a method, device and equipment for generating a digital surface model that takes into account both plane and elevation, so as to effectively solve the problems of incorrect plane position of the digital surface model extracted by InSAR and inconsistent elevation values ​​in overlapping areas when there are no ground control points and it is difficult to obtain accurate InSAR orbital state vector information, so as to realize the joint application of digital surface models extracted by InSAR in large areas.

[0007] In a first aspect, an embodiment of the present invention provides a method for generating a digital surface model taking into account both plane and elevation, comprising:

[0008] Obtain InSAR interferometric pairs, reference DEM data and optical reference benchmarks corresponding to the study area;

[0009] Combined with the reference DEM data and the optical reference datum, the rational polynomial parameter solution processing, the automatic extraction processing of the control points and the connection points, and the plane adjustment solution processing are performed on the InSAR interferometer pair to obtain the geometric correction parameters corresponding to the InSAR interferometer pair; and the baseline calculation processing is performed on the InSAR interferometer pair to obtain the initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase;

[0010] Based on the reference DEM data, optical reference datum and geometric correction parameters, the elevation correction control points are extracted from the InSAR interferometer pair, so as to refine the initial baseline using the elevation correction control points and obtain the target baseline.

[0011] Based on the geometric correction parameters and the target baseline, the unwrapped phase is subjected to phase height conversion processing to convert the unwrapped phase into the target digital surface model corresponding to the study area.

[0012] In one embodiment, the elevation correction control points are extracted from the InSAR interferometer pair based on the reference DEM data, the optical reference benchmark and the geometric correction parameters, so as to refine the initial baseline using the elevation correction control points to obtain the target baseline, including:

[0013] According to the geometric correction parameters, the InSAR interferometer pair is geometrically corrected to obtain the precise geometric geographic range of the image;

[0014] Using reference DEM data and optical reference datum as reference, the elevation correction control points are extracted from the InSAR interferometric pairs based on the precise geometric geographic extent of the images;

[0015] According to the coherence of the corresponding images of InSAR interferometry, the height correction control points are screened to obtain the target height correction control points;

[0016] The target elevation correction control points are used to refine the initial baseline to obtain the target baseline.

[0017] In one implementation, the initial baseline is refined using the target elevation correction control points to obtain the target baseline, including:

[0018] The least square method is used to fit the baseline refinement function based on the target elevation correction control points, and the initial baseline is input into the baseline refinement function to obtain the target baseline output by the baseline refinement function.

[0019] In one embodiment, based on the geometric correction parameters and the target baseline, the unwrapped phase is subjected to phase height conversion processing to convert the unwrapped phase into a target digital surface model corresponding to the study area, including:

[0020] Through the phase height conversion model, the unwrapped phase is processed based on the target baseline to convert the unwrapped phase into an initial digital surface model corresponding to the study area;

[0021] The initial digital surface model is transformed using geometric correction parameters to obtain the target digital surface model corresponding to the study area.

[0022] In one implementation, in combination with reference DEM data and optical reference datum, rational polynomial parameter solution processing, automatic extraction processing of control points and tie points, and plane adjustment solution processing are performed on the InSAR interferometer pair to obtain geometric correction parameters corresponding to the InSAR interferometer pair, including:

[0023] Extract the rigorous imaging model of the InSAR interferometer pair, and use the rigorous imaging model to solve the rational polynomial parameters of the InSAR interferometer pair to obtain the rational polynomial parameters;

[0024] Using rational polynomial parameters and reference DEM data, the main image in the InSAR interferometer pair is pre-orthorectified to obtain the initial geometric location of the image.

[0025] With reference to the DEM data and optical reference datum, the control points and connection points of the InSAR interferometer are automatically extracted and processed based on the initial geometrical geographic location of the image to obtain the initial control points and initial connection points.

[0026] The InSAR interferometer pair is processed by plane adjustment using the initial control points and initial connection points to obtain the corresponding geometric correction parameters of the InSAR interferometer pair.

[0027] In one embodiment, performing baseline calculation processing on the InSAR interferometer pair to obtain an initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase includes:

[0028] According to the position, velocity and time information of the InSAR interferometer pair, a position polynomial model and a velocity polynomial model are fitted respectively, so as to determine the satellite position vector corresponding to any position in the image included in the InSAR interferometer pair based on the position polynomial model, and to determine the instantaneous velocity vector of the antenna center corresponding to any position in the image included in the InSAR interferometer pair based on the velocity polynomial model;

[0029] Based on the satellite position vector and the instantaneous velocity vector of the antenna center, the initial baseline corresponding to the InSAR interferometer pair is determined, and the unwrapped phase is extracted based on the initial baseline.

[0030] In a second aspect, an embodiment of the present invention further provides a device for generating a digital surface model taking into account both plane and elevation, comprising:

[0031] Data acquisition module, used to obtain InSAR interferometric pairs, reference DEM data and optical reference benchmarks corresponding to the study area;

[0032] The data processing module is used to combine the reference DEM data and the optical reference benchmark to perform rational polynomial parameter solution processing, automatic extraction processing of control points and connection points, and plane adjustment solution processing on the InSAR interferometer pair to obtain the geometric correction parameters corresponding to the InSAR interferometer pair; and perform baseline calculation processing on the InSAR interferometer pair to obtain the initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase;

[0033] The baseline refinement module is used to extract the elevation correction control points from the InSAR interferometer pair based on the reference DEM data, the optical reference benchmark and the geometric correction parameters, so as to refine the initial baseline using the elevation correction control points to obtain the target baseline;

[0034] The digital surface model generation module is used to perform phase height conversion processing on the unwrapped phase based on the geometric correction parameters and the target baseline, so as to convert the unwrapped phase into a target digital surface model corresponding to the study area.

[0035] In one implementation, the baseline refinement module is specifically used to:

[0036] According to the geometric correction parameters, the InSAR interferometer pair is geometrically corrected to obtain the precise geometric geographic range of the image;

[0037] Using reference DEM data and optical reference datum as reference, the elevation correction control points are extracted from the InSAR interferometric pairs based on the precise geometric geographic extent of the images;

[0038] According to the coherence of the corresponding images of InSAR interferometry, the height correction control points are screened to obtain the target height correction control points;

[0039] The target elevation correction control points are used to refine the initial baseline to obtain the target baseline.

[0040] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement any one of the methods provided in the first aspect.

[0041] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement any one of the methods provided in the first aspect.

[0042] The embodiment of the present invention provides a method, device and equipment for generating a digital surface model taking both plane and elevation into consideration. First, an InSAR interferometer pair, reference DEM data and an optical reference benchmark corresponding to a study area are obtained; then, in combination with the reference DEM data and the optical reference benchmark, rational polynomial parameter solution processing, control point and connection point automatic extraction processing, and plane adjustment solution processing are performed on the InSAR interferometer pair to obtain geometric correction parameters corresponding to the InSAR interferometer pair; and baseline calculation processing is performed on the InSAR interferometer pair to obtain an initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase; then, based on the reference DEM data, the optical reference benchmark and the geometric correction parameters, elevation correction control points are extracted from the InSAR interferometer pair to refine the initial baseline using the elevation correction control points to obtain a target baseline; finally, based on the geometric correction parameters and the target baseline, phase height conversion processing is performed on the unwrapped phase to convert the unwrapped phase into a target digital surface model corresponding to the study area. The method realizes accurate correction of the plane position of the digital surface model extracted by InSAR through rational polynomial parameter solution technology, automatic extraction technology of InSAR image control points and connection points, and InSAR image plane adjustment technology; on this basis, the elevation correction control point selection technology, InSAR baseline refinement technology, phase height conversion technology, etc. based on reference DEM data are used to realize the joint correction of the elevation of the InSAR digital surface model. The embodiment of the present invention finally realizes the production of a large-area InSAR digital surface model with accurate plane position and consistent elevation values ​​in overlapping areas, solves the problem of adjustment of InSAR digital surface models without ground control points, and can meet the high-precision and high-efficiency requirements of the production of large-scale InSAR digital surface models.

[0043] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0044] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1A schematic diagram of a flow chart of a method for generating a digital surface model taking both plane and elevation into consideration provided by an embodiment of the present invention;

[0047] Figure 2 An overall flow chart of a method for generating a digital surface model taking both plane and elevation into consideration provided by an embodiment of the present invention;

[0048] Figure 3 An InSAR image point distribution map provided by an embodiment of the present invention;

[0049] Figure 4 An example diagram of target elevation correction control points provided by an embodiment of the present invention;

[0050] Figure 5 An InSAR image distribution map provided by an embodiment of the present invention;

[0051] Figure 6 An ICESat / GLAS laser altimetry point distribution map provided by an embodiment of the present invention;

[0052] Figure 7 A DSM result map obtained by using a method for generating a digital surface model taking both plane and elevation into consideration provided by an embodiment of the present invention;

[0053] Figure 8 A DSM result diagram obtained by conventional methods provided in an embodiment of the present invention;

[0054] Fig. 9 An elevation accuracy evaluation diagram provided by an embodiment of the present invention;

[0055] Fig.10 A pixel distribution map with an elevation difference within 5 meters provided in an embodiment of the present invention;

[0056] Fig.11 A pixel distribution map with an elevation difference within 10 meters provided in an embodiment of the present invention;

[0057] Fig.12 A schematic diagram of the structure of a digital surface model generation device taking both plane and elevation into consideration provided by an embodiment of the present invention;

[0058] Fig.13 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described in combination with the embodiments below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] At present, the existing InSAR DSM extraction adjustment methods all require the use of ground control points, and do not mention the joint correction of the plane position of the InSAR DSM and the InSAR DSM extraction adjustment method without ground control points. For areas lacking high-precision three-dimensional coordinates and ground control, it is impossible to obtain the InSAR DSM results of the plane position and elevation joint correction. Based on this, the present invention implements a method, device and equipment for generating a digital surface model that takes both plane and elevation into consideration, which effectively solves the problem of the plane position error of the digital surface model extracted by InSAR and the inconsistent elevation values ​​in the overlapping area when there are no ground control points and it is difficult to obtain accurate InSAR orbital state vector information, and realizes the joint application of the digital surface model extracted by InSAR in a large area.

[0061] To facilitate understanding of this embodiment, firstly, a method for generating a digital surface model taking into account both plane and elevation disclosed in an embodiment of the present invention is described in detail. Figure 1 The flowchart of a method for generating a digital surface model taking both plane and elevation into consideration is shown in FIG. 1 , and the method mainly includes the following steps S102 to S108:

[0062] Step S102, obtaining the InSAR interferometric pair, reference DEM (Digital Elevation Model) data and optical reference datum corresponding to the study area, wherein the InSAR interferometric pair includes an InSAR primary image and an InSAR auxiliary image.

[0063] Step S104, combining the reference DEM data and the optical reference datum, performing rational polynomial parameter solution processing, control point and tie point automatic extraction processing, and plane adjustment solution processing on the InSAR interferometer pair to obtain the geometric correction parameters corresponding to the InSAR interferometer pair; and performing baseline calculation processing on the InSAR interferometer pair to obtain the initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase.

[0064] In one example, a rigorous imaging geometry model of the InSAR image is extracted, the correspondence between the three-dimensional spatial grid of ground points and the image surface is established, the rational polynomial (RPC, Remote Procedure Call) parameters of the InSAR master image are solved, and the initial geometric geographic range of the InSAR master image is obtained; the optical reference benchmark and external reference DEM data within the initial geometric geographic range of the InSAR image are used to automatically extract the InSAR image control points and the connection points between the InSAR images through a heterogeneous matching algorithm; the automatically obtained connection points and control points are used as the InSAR image plane adjustment control points and connection points, and the regional network adjustment is performed to obtain the geometric correction parameters (RPC+RPC optimization coefficient) of the InSAR image, thereby improving the absolute plane positioning accuracy of the InSAR image in the region and the relative accuracy between images.

[0065] In one example, DSM is extracted based on InSAR technology, which mainly includes image registration, interferogram calculation, coherence map calculation, deflating interferogram generation, interferogram filtering, phase unwrapping, etc. The InSAR interferogram pairs are processed to obtain the initial baseline and its corresponding unwrapped phase.

[0066] Step S106, extracting elevation correction control points from the InSAR interferometer pair based on the reference DEM data, the optical reference benchmark and the geometric correction parameters, so as to refine the initial baseline using the elevation correction control points to obtain the target baseline;

[0067] In one example, based on the joint correction of the InSAR image planar position, the precise geometric geographic range of the InSAR image is calculated, and the elevation correction control points of the InSAR image are obtained by image matching on the external reference DEM. According to the geometric correction parameters of the InSAR image, the radar (range Doppler) coordinates corresponding to the elevation correction control points of the InSAR image are obtained, and then the control point information required for InSAR baseline refinement is generated. This point selection method ensures that the overlapping areas of adjacent InSAR images have the same elevation control points, which can further reduce the elevation differences in the overlapping areas of InSAR DSM and ensure subsequent effective stitching. Using the baseline refinement control point information, based on the least squares baseline refinement model, the orbit vector of the initial baseline is refined to obtain the baseline vector and rate of each InSAR image, that is, the target baseline.

[0068] Step S108, performing phase height conversion processing on the unwrapped phase based on the geometric correction parameters and the target baseline, so as to convert the unwrapped phase into a target digital surface model corresponding to the study area.

[0069] In one example, the refined target baseline is used to perform phase height conversion on the unwrapped phase formed by each InSAR image processing to extract the initial digital surface model in the radar coordinate system (referred to as the initial DSM result). The geometric correction parameters of the InSAR image are used to perform geometric correction on the initial DSM result of the radar coordinate system extracted by InSAR processing to obtain the target digital surface model after plane adjustment and elevation correction (referred to as the target DSM result).

[0070] The digital surface model generation method that takes both plane and elevation into consideration provided by the embodiment of the present invention realizes accurate correction of the plane position of the digital surface model extracted by InSAR through rational polynomial parameter solution technology, InSAR image control point and connection point automatic extraction technology, and InSAR image plane adjustment technology; on this basis, the elevation correction control point selection technology, InSAR baseline refinement technology, phase height conversion technology, etc. based on reference DEM data are used to realize the joint correction of the elevation of the InSAR digital surface model. The embodiment of the present invention finally realizes the production of a large-area InSAR digital surface model with accurate plane position and consistent elevation values ​​in overlapping areas, solves the problem of adjustment of InSAR digital surface models without ground control points, can meet the high-precision and high-efficiency requirements of the production of large-scale InSAR digital surface models, and can be applied to surveying and mapping, hydrology, meteorology, geomorphology, geology, soil, engineering construction, communications, military and other national economy and national defense construction as well as humanities and natural sciences.

[0071] For ease of understanding, the embodiments of the present invention provide Figure 2 The overall flow chart of a method for generating a digital surface model that takes both plane and elevation into consideration is shown in FIG. 1 , including: for N interference pairs, extracting a rigorous imaging model of the InSAR image, establishing a control grid and a detection grid, solving RPC parameters, iterating and correcting the RPC parameters, so as to obtain the initial geometric geographic range of the image; combining reference DEM data and optical reference datum, extracting the connection points of the interference pairs and generating the control points of the interference pairs, performing plane adjustment of the interference pairs based on the connection points of the interference pairs and the control points of the interference pairs, obtaining the geometric correction parameters of the InSAR image and the precise geometric geographic range between the interference pairs, and obtaining the initial geometric geographic range based on the precise geometric geographic range. Take the elevation correction control points, and further screen out the baseline refinement control points (i.e., target elevation correction control points); in addition, obtain the compensated phase (i.e., unwrapped phase) through operations such as primary and auxiliary image registration, interference calculation, calculation of the initial baseline, removal of flat ground phase, phase simulation, phase difference, phase filtering and unwrapping, and phase compensation; refine the initial baseline through the aforementioned baseline refinement control points to obtain accurate baseline information (i.e., target baseline), perform phase-to-elevation operations in combination with the aforementioned compensation phase, and then perform coordinate conversion operations in combination with the InSAR image geometric correction parameters to obtain the final DEM results.

[0072] exist Figure 2 On this basis, an embodiment of the present invention provides a specific implementation method of a method for generating a digital surface model taking into account both plane and elevation.

[0073] For the aforementioned step S104, an embodiment of the present invention provides a specific step of combining reference DEM data and optical reference datum, performing rational polynomial parameter solution processing, automatic extraction processing of control points and connection points, and plane adjustment solution processing on the InSAR interferometer pair, and obtaining geometric correction parameters corresponding to the InSAR interferometer pair.

[0074] Among them, the InSAR image plane adjustment can obtain the precise geometric correction parameters (PRC+RPC optimization coefficients) of the InSAR image and provide a correction model for the plane adjustment of InSAR DSM extraction.

[0075] In the specific implementation, please refer to the following steps 1A to 1C:

[0076] Step 1A, extracting the rigorous imaging model of the InSAR interferometer pair, performing rational polynomial parameter solving processing on the InSAR interferometer pair through the rigorous imaging model, and obtaining rational polynomial parameters.

[0077] In one example, the process of solving the RPC parameters of the InSAR main image is as follows:

[0078] According to the strict imaging model of the InSAR main image, the geographical range of the InSAR main image is calculated; with the help of external reference DEM data, the maximum and minimum elevations of the geographical range are obtained; in the elevation direction of the range, the layers are layered at certain intervals, and on the plane, a ground regular grid is established with a certain grid size to generate the control point coordinates for RPC parameter solution; using the generated control point coordinates, the RPC parameters are fitted and calculated. The calculation formula is as follows:

[0079] ;

[0080] ;

[0081] Among them, (r, c) represents the azimuth and range image coordinates of the InSAR image, and (P, L, H) represents the corresponding geographic coordinates longitude, latitude and altitude. In order to prevent the matrix from being ill-conditioned during algorithm operation, (r, c, P, L, H) is normalized. Nr, NC, Dr and Dc are polynomial functions.

[0082] Step 1B, using rational polynomial parameters and reference DEM data, pre-orthogonal processing is performed on the main image in the InSAR interferometry pair to obtain the initial geometric geographic location of the InSAR interferometry pair; using the reference DEM data and optical reference benchmark as a reference, the control points and connection points of the InSAR interferometry pair are automatically extracted based on the initial geometric geographic location of the image to obtain the initial control points and initial connection points.

[0083] In one example, the process of automatic extraction of InSAR main image points is as follows:

[0084] The InSAR main image is pre-orthogonally processed using the solved RPC of the InSAR main image and the external reference DEM data to obtain the initial geometric geographic location of the InSAR main image; the control points and connection points required for the InSAR image adjustment are extracted based on the optical reference benchmark and external reference DEM data.

[0085] In the specific implementation, the automatic extraction of control points includes two steps: feature point extraction and homonymous point recognition. Feature point extraction: using the Harris operator, based on the block extraction strategy, a large number of evenly distributed feature points are extracted on the optical reference image; homonymous point recognition: using mutual information as a similarity measure, a two-way matching strategy is used on the InSAR main image to recognize homonymous points.

[0086] (1) Feature point extraction: Divide the optical reference into n*n non-overlapping grids, and calculate the Harris value of each pixel in each grid. Sort the calculated Harris operators from large to small, set the threshold T, and take the pixels that meet the threshold condition as feature points.

[0087] Harris operator is a detection operator based on the signal autocorrelation function, and its expression is as follows:

[0088] ;

[0089] In the formula, M represents the gradient of the pixel location to form the autocorrelation matrix; Represents the gradient in the x direction; Represents the gradient in the y direction; The scale is Gaussian convolution kernel; * represents convolution operation;

[0090] The numerical calculation formula of Harris operator is as follows:

[0091] ;

[0092] In the formula, I represents the corner point response value; Det represents the determinant of the matrix; Trace is the trace of the matrix; K is the default constant. A corner point is when the I of a pixel is greater than the set threshold T and is a local maximum.

[0093] (2) Identification of homonymous points: For the feature point P1 on the optical reference datum, the template matching method is used to find the corresponding matching point P2 on the InSAR image according to the principle of maximizing the similarity measure. In the same way, the matching point p3 corresponding to P2 is found on the optical reference datum. If p1 and p3 are less than 1.5 pixels, (P1, P2) is considered to be a pair of homonymous points, otherwise it is deleted as a mismatched point. Since the longitude and latitude of the optical reference datum point are known, the homonymous points extracted on the InSAR image can be used as control points for InSAR adjustment. The calculation formula for the similarity measure is as follows:

[0094] ;

[0095] in, and are the entropies of image A and image B respectively, represents their joint entropy. The entropy calculation formula is as follows:

[0096] ;

[0097] ;

[0098] ;

[0099] in, and represents the marginal probability distribution, represents the joint probability distribution. The calculation formula of probability distribution is as follows:

[0100] ;

[0101] ;

[0102] .

[0103] In the formula, Represents the joint histogram between two images.

[0104] In the specific implementation, the connection point automatic extraction is mainly realized by extracting the connection points between InSAR images, and only the row and column number information of the points is recorded. The algorithm is the same as the InSAR image control point extraction. The principle is as above, and the embodiment of the present invention will not be repeated here.

[0105] Step 1C: using the initial control points and the initial connection points, perform plane adjustment on the InSAR interferometer pair to obtain the geometric correction parameters corresponding to the InSAR interferometer pair.

[0106] In one example, the process of planar block adjustment of InSAR images is as follows:

[0107] The InSAR image planar block adjustment calculates the affine transformation parameters of each InSAR image by automatically matching the ground coordinates of the control points and their planar coordinates on the InSAR image. The InSAR image RPC model is spatially resected using the extracted connection points and control points to solve the directional parameters, refine the RPC model, and obtain the RPC optimization coefficient.

[0108] The affine transformation formula on InSAR images is as follows:

[0109] ;

[0110] ;

[0111] Among them, (x, y) is the column number and row number of the control point on the InSAR image, (sample, line) is the coordinate column number and row number of the control point projected onto the image using the RPC parameters, ( )(i=0,1,2) are the affine transformation coefficients.

[0112] For each tie point and control point, the corresponding error method is as follows:

[0113] ;

[0114] ( , is the RPC optimization coefficient, ( , , ) is the correction value of the object coordinates of the connection point or ground control point, and When taking initial values ​​for the unknowns and The value of .

[0115] ;

[0116] in, and is the affine transformation coefficient and object coordinate matrix, and The corresponding coefficient matrix is, is the corresponding constant vector, is the weight matrix.

[0117] For the coordinates of the ground control points, they are treated as weighted observations and the following error equation needs to be established:

[0118] ;

[0119] Among them, (lat, lon, height) is the measured coordinates of the ground control point, The corresponding approximate value is taken in the first iterative calculation, and the corresponding measurement coordinate is taken.

[0120] For the aforementioned step S104, the embodiment of the present invention further provides a specific step of performing baseline calculation processing on the InSAR interferometer pair to obtain an initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase.

[0121] In practical applications, the baseline parameter error has a great influence on the accuracy of the interferometric phase inversion ground point elevation. Usually, the inaccurate baseline parameter estimation will lead to a more obvious "slope" effect in the acquisition, so accurate baseline estimation is required.

[0122] For details, please refer to Step 2A to Step 2B below:

[0123] Step 2A, according to the position, velocity, and time information of the InSAR interferometer pair, respectively fit the position polynomial model and the velocity polynomial model, so as to determine the satellite position vector corresponding to any position in the image included in the InSAR interferometer pair based on the position polynomial model, and determine the antenna center instantaneous velocity vector corresponding to any position in the image included in the InSAR interferometer pair based on the velocity polynomial model. Specifically:

[0124] (1) Based on the position, velocity and time information provided by the satellite ephemeris of the primary and secondary InSAR satellites, a polynomial model of the satellite position and velocity changing with time is fitted using a cubic polynomial. The satellite state vector corresponding to any pixel in the image is calculated using the model. The position polynomial model is as follows:

[0125] ;

[0126] In the model , , is the satellite position vector; t is the time; , , (i=1,2,3) are unknown fitting coefficients,

[0127] There are 12 unknown fitting coefficients in this model, which can be solved by the least squares method using the known positions and times of 4 or more points.

[0128] (2) After obtaining the model coefficients, the following formula can be used to calculate the instantaneous velocity vector of the antenna center corresponding to any position in the image: , the velocity polynomial model is as follows:

[0129] .

[0130] Step 2B, based on the satellite position vector and the antenna center instantaneous velocity vector, determine the initial baseline corresponding to the InSAR interferometer pair, and extract the unwrapped phase based on the initial baseline. In practical applications, the initial baseline can be obtained based on the precise matching parameters of the main and auxiliary images and the calculated position polynomial model and velocity polynomial model.

[0131] For the aforementioned step S106, an embodiment of the present invention provides a specific step of extracting elevation correction control points from an InSAR interferometer pair based on reference DEM data, an optical reference benchmark and geometric correction parameters, so as to use the elevation correction control points to refine the initial baseline and obtain a target baseline.

[0132] In practical applications, the accuracy of the InSAR initial baseline parameters calculated based on satellite ephemeris parameters is not high. In order to obtain high-precision DSM results, the initial baseline needs to be refined.

[0133] The existing control point-based baseline estimation method can accurately solve the orientation parameters of the image by using the ground control points through the image model equation and the earth model equation, and then calculate the antenna center position coordinates at the specified pixel according to the precise matching parameters of the main and auxiliary images, so as to calculate the baseline parameters; for the case where there are sufficient control points in the image coverage area, the baseline estimation accuracy of this method is higher, but for difficult areas such as unmapped areas, it is difficult to use this method for effective baseline parameter estimation due to the lack of control points; at the same time, this method refines the interferometric baseline from the perspective of a single InSAR interferometric pair, which is not conducive to eliminating the relative errors between multiple InSAR DSMs.

[0134] In view of the above problems, the embodiment of the present invention uses the precise geometric correction parameters (PRC+RPC optimization coefficients) of the InSAR image obtained by the plane adjustment of the InSAR image, and based on the external reference DEM data, jointly extracts the InSAR interferometric baseline refinement control points, and screens the control points according to the InSAR coherence information, and finally uses the obtained control points to achieve high-precision correction of the InSAR baseline error. For details, please refer to the following steps 3A to 3D:

[0135] Step 3A, geometrically correct the InSAR interferometer pair according to the geometric correction parameters to obtain the precise geometric geographic range of the image. Specifically, geometrically correct the SAR image according to the geometric correction parameters obtained by the InSAR image adjustment to obtain the precise geometric geographic range of the image.

[0136] Step 3B, using the reference DEM data and optical reference benchmark as reference, extract the elevation correction control points from the InSAR interferometric pair based on the precise geometric geographic range of the image. Specifically, using the external reference DEM data and optical reference benchmark as reference, using the image matching algorithm, extract the control points (longitude (lon), latitude (lat), elevation (height)) of each InSAR image, as well as the connection points (longitude (lon), latitude (lat), elevation (height)) between InSAR images, such as Figure 3 An InSAR image point distribution map is shown, in which light gray represents the extracted control points and dark gray represents the extracted connection points.

[0137] Step 3C: Screen the elevation correction control points according to the coherence of the corresponding InSAR interferometric images to obtain the target elevation correction control points.

[0138] Specifically, according to the geometric correction parameters of each InSAR image, the control points and connection points extracted in the above steps are converted into the row and column number information of the InSAR image. And according to the coherence information of the InSAR image, the control points with coherence less than 0.3 are eliminated to obtain the control points (image column number, image row number, elevation value) required for the InSAR image baseline refinement, that is, the target elevation correction control points, such as Figure 4 An example diagram of target elevation correction control points is shown.

[0139] Step 3D, using the target elevation correction control points to refine the initial baseline to obtain the target baseline. In one embodiment, the least squares method can be used to fit the baseline refinement function based on the target elevation correction control points, and the initial baseline is input into the baseline refinement function to obtain the target baseline output by the baseline refinement function.

[0140] Specifically, the baseline is refined using the baseline estimation method derived in the TCN (track tangent, perpendicular to the track direction, and normal direction) coordinate system. The principle is as follows:

[0141] ;

[0142] In the formula, is the unwrapped phase of pixel i, are the components of the slant distance vector and the baseline in the normal direction of pixel i, is the component of the slant distance vector of pixel i in the direction perpendicular to the track, is the imaging time of pixel i, is the component of the baseline in the normal direction (not constant in the entire image), the coefficient It is used to correct the normal component of the baseline caused by the non-parallel tracks. is the phase constant.

[0143] Through the control points extracted above, the least squares equation is established, and the three unknowns in the above formula are calculated iteratively. , , , and finally obtain the accurate InSAR baseline vector, which is the refined target baseline.

[0144] For the aforementioned step S108, the embodiment of the present invention provides a specific step of performing phase height conversion processing on the unwrapped phase based on the geometric correction parameters and the target baseline to convert the unwrapped phase into a target digital surface model corresponding to the study area. For details, please refer to the following steps 4A to 4B:

[0145] Step 4A, using the phase height conversion model, performs phase height conversion processing on the unwrapped phase based on the target baseline to convert the unwrapped phase into an initial digital surface model corresponding to the study area.

[0146] In the specific implementation, DSM is extracted based on InSAR technology, which mainly includes image registration, interference pattern calculation, coherence pattern calculation, deflating interference pattern generation, interference pattern filtering, phase unwrapping, phase elevation conversion and geocoding. Among them, the steps of image registration, interference pattern calculation, coherence pattern calculation, deflating interference pattern generation, interference pattern filtering and phase unwrapping adopt conventional general algorithms; the InSAR baseline correction results are used in the phase-to-elevation conversion to convert the unwrapped phase into the DSM result. The phase-to-elevation conversion formula is as follows:

[0147] ;

[0148] in, is the radar wavelength, is the slope distance, is the incident angle, is the unwrapped phase, It is the vertical baseline length calculated based on the baseline correction result.

[0149] According to the above formula, the InSAR DSM result after elevation correction is obtained, which is also the initial digital representative model.

[0150] Step 4B: perform coordinate transformation processing on the initial digital surface model using the geometric correction parameters to obtain a target digital surface model corresponding to the study area.

[0151] In the specific implementation, the DSM result calculated by the "InSAR DSM" extraction step is the radar coordinates. The InSAR geometric correction coefficients obtained by the "InSAR image adjustment" are used to transform the DSM of the radar coordinate system to obtain the DSM result after plane adjustment, which is the target digital surface model.

[0152] In summary, the embodiment of the present invention optimizes the InSAR DSM extraction process by utilizing optical reference benchmarks, external reference DEM data, InSAR image strict imaging models, and InSAR interference information based on RPC solution technology, InSAR image control point and connection point automatic extraction technology, InSAR image plane adjustment technology, InSAR baseline correction technology, phase height conversion technology, etc., to achieve the plane and elevation joint correction of InSAR DSM results, and obtain large-area InSAR DSM results with accurate plane positions and consistent elevation values ​​in overlapping areas. A high-precision joint application of large-scale InSAR DSM results is achieved. The method for generating a digital surface model that takes into account both plane and elevation provided by the embodiment of the invention is verified by processing and extracting DSM with 9 InSAR interference pairs:

[0153] The data is shown in Table 1 below:

[0154] Table 1 Experimental data description

[0155]

[0156] Geometric accuracy verification: The geometric position of the DSM image extracted by InSAR is consistent with that of the InSAR main image. Corresponding points of the same name are set on the InSAR main image and the optical benchmark as checkpoints. The error value between the checkpoint coordinates (x1, y1) in the InSAR image and the coordinates (x, y) of the optical benchmark image data is calculated to obtain the accuracy verification results, as shown in Table 2.

[0157] Table 2 Geometric accuracy inspection results

[0158]

[0159] Absolute height accuracy verification: see Figure 6 The ICESat / GLAS laser altimetry point distribution map shown in the figure uses ICESat / GLAS laser altimetry data and removes control points in low-coherence areas such as overlapped areas, shadow areas, and water areas to verify the DSM elevation accuracy. The verification results are as follows, including: Figure 7 The DSM result map shown is obtained by using a digital surface model generation method that takes both plane and elevation into consideration. Figure 8 A DSM result obtained by conventional method is shown in Table 3, an elevation accuracy evaluation result is shown in Table 3, and the following is provided based on Table 3: Fig. 9 An elevation accuracy evaluation diagram shown includes a mean error comparison and a mean error comparison.

[0160] Table 3 Elevation accuracy evaluation results

[0161]

[0162] Relative elevation accuracy verification: The relative elevation accuracy is verified by statistically analyzing the DSM difference between the overlapping area of ​​image 1 and image 2 of the method provided by the embodiment of the present invention and the conventional InSAR method. The results include: a statistical table of pixels with elevation difference within 5 meters as shown in Table 4, Fig.10 A distribution map of pixels with elevation differences within 5 meters is shown in Table 5, and a statistical table of pixels with elevation differences within 10 meters is shown in Table 5. Fig.11 The figure shows a distribution map of pixels with elevation differences within 10 meters.

[0163] Table 4 Statistics of pixels with elevation difference within 5 meters

[0164]

[0165] Table 5 Statistics of pixels with elevation difference within 10 meters

[0166]

[0167] In summary. The DSM generated by the method provided by the embodiment of the present invention has improved geometric accuracy and elevation accuracy compared with conventional InSAR DSM results. This method can realize the joint correction of the plane and elevation of InSAR DSM results, and obtain large-area InSAR DSM results with accurate plane positions and consistent elevation values ​​in overlapping areas. It can realize the high-precision joint application of large-scale InSAR DSM results.

[0168] Based on the above embodiments, the present invention provides a digital surface model generation device that takes both plane and elevation into consideration. Fig.12 The structure diagram of a digital surface model generation device taking into account both plane and elevation is shown, and the device mainly includes the following parts:

[0169] The data acquisition module 1202 is used to obtain the InSAR interferometric pairs, reference DEM data and optical reference datum corresponding to the study area;

[0170] The data processing module 1204 is used to combine the reference DEM data and the optical reference benchmark to perform rational polynomial parameter solution processing, automatic extraction processing of control points and tie points, and plane adjustment solution processing on the InSAR interferometer pair to obtain geometric correction parameters corresponding to the InSAR interferometer pair; and perform baseline calculation processing on the InSAR interferometer pair to obtain the initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase;

[0171] A baseline refinement module 1206 is used to extract elevation correction control points from the InSAR interferometric pair based on reference DEM data, optical reference datum and geometric correction parameters, so as to refine the initial baseline using the elevation correction control points to obtain a target baseline;

[0172] The digital surface model generation module 1208 is used to perform phase height conversion processing on the unwrapped phase based on the geometric correction parameters and the target baseline, so as to convert the unwrapped phase into a target digital surface model corresponding to the study area.

[0173] The digital surface model generation method that takes both plane and elevation into consideration provided by the embodiment of the present invention realizes accurate correction of the plane position of the digital surface model extracted by InSAR through rational polynomial parameter solution technology, automatic extraction technology of InSAR image control points and connection points, and InSAR image plane adjustment technology; on this basis, the elevation correction control point selection technology, InSAR baseline refinement technology, phase height conversion technology, etc. based on reference DEM data are used to realize joint correction of the elevation of the InSAR digital surface model. The embodiment of the present invention ultimately realizes the production of a large-area InSAR digital surface model with accurate plane position and consistent elevation values ​​in overlapping areas, solves the problem of adjustment of InSAR digital surface models without ground control points, and can meet the high-precision and high-efficiency requirements of large-scale InSAR digital surface model production.

[0174] In one implementation, the baseline refinement module 1206 is specifically configured to:

[0175] According to the geometric correction parameters, the InSAR interferometer pair is geometrically corrected to obtain the precise geometric geographic range of the image;

[0176] Using reference DEM data and optical reference datum as reference, the elevation correction control points are extracted from the InSAR interferometric pairs based on the precise geometric geographic extent of the images;

[0177] According to the coherence of the corresponding images of InSAR interferometry, the height correction control points are screened to obtain the target height correction control points;

[0178] The target elevation correction control points are used to refine the initial baseline to obtain the target baseline.

[0179] In one implementation, the baseline refinement module 1206 is specifically configured to:

[0180] The least square method is used to fit the baseline refinement function based on the target elevation correction control points, and the initial baseline is input into the baseline refinement function to obtain the target baseline output by the baseline refinement function.

[0181] In one implementation, the digital surface model generation module 1208 is specifically used to:

[0182] Through the phase height conversion model, the unwrapped phase is processed based on the target baseline to convert the unwrapped phase into an initial digital surface model corresponding to the study area;

[0183] The initial digital surface model is transformed using geometric correction parameters to obtain the target digital surface model corresponding to the study area.

[0184] In one implementation, the data processing module 1204 is specifically configured to:

[0185] Extract the rigorous imaging model of the InSAR interferometer pair, and use the rigorous imaging model to solve the rational polynomial parameters of the InSAR interferometer pair to obtain the rational polynomial parameters;

[0186] Using rational polynomial parameters and reference DEM data, the main image in the InSAR interferometer pair is pre-orthorectified to obtain the initial geometric location of the image.

[0187] With reference to the DEM data and optical reference datum, the control points and connection points of the InSAR interferometer are automatically extracted and processed based on the initial geometrical geographic location of the image to obtain the initial control points and initial connection points.

[0188] The InSAR interferometer pair is processed by plane adjustment using the initial control points and initial connection points to obtain the corresponding geometric correction parameters of the InSAR interferometer pair.

[0189] In one implementation, the data processing module 1204 is specifically configured to:

[0190] According to the position, velocity and time information of the InSAR interferometer pair, a position polynomial model and a velocity polynomial model are fitted respectively, so as to determine the satellite position vector corresponding to any position in the image included in the InSAR interferometer pair based on the position polynomial model, and to determine the instantaneous velocity vector of the antenna center corresponding to any position in the image included in the InSAR interferometer pair based on the velocity polynomial model;

[0191] Based on the satellite position vector and the instantaneous velocity vector of the antenna center, the initial baseline corresponding to the InSAR interferometer pair is determined, and the unwrapped phase is extracted based on the initial baseline.

[0192] The device provided in the embodiment of the present invention has the same implementation principle and technical effects as those of the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0193] An embodiment of the present invention provides an electronic device. Specifically, the electronic device includes a processor and a storage device. The storage device stores a computer program, and when the computer program is executed by the processor, it executes the method described in any one of the above-mentioned implementation methods.

[0194] Fig.13 A structural diagram of an electronic device provided in an embodiment of the present invention, the electronic device 100 includes: a processor 130, a memory 131, a bus 132 and a communication interface 133, wherein the processor 130, the communication interface 133 and the memory 131 are connected via the bus 132; the processor 130 is used to execute an executable module stored in the memory 131, such as a computer program.

[0195] The memory 131 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 133 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0196] The bus 132 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.13 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0197] Among them, the memory 131 is used to store programs, and the processor 130 executes the program after receiving the execution instruction. The method executed by the device for flow process definition disclosed in any of the embodiments of the present invention can be applied to the processor 130 or implemented by the processor 130.

[0198] The processor 130 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 130. The above processor 130 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), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiment of the present invention can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module may be located in a storage medium mature in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 131, and the processor 130 reads the information in the memory 131 and completes the steps of the above method in combination with its hardware.

[0199] The computer program product of the readable storage medium provided in the embodiment of the present invention includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the methods described in the previous method embodiments. The specific implementation can be referred to the previous method embodiments, which will not be repeated here.

[0200] If the functions are implemented in the form of software functional units 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 the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0201] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for generating a digital surface model taking into account both plane and elevation, characterized in that: include: Obtain InSAR interferometric pairs, reference DEM data and optical reference benchmarks corresponding to the study area; In combination with the reference DEM data and the optical reference benchmark, the InSAR interferometer pair is subjected to rational polynomial parameter solution processing, control point and tie point automatic extraction processing, and plane adjustment solution processing to obtain geometric correction parameters corresponding to the InSAR interferometer pair; and the InSAR interferometer pair is subjected to baseline calculation processing to obtain an initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase; Extracting elevation correction control points from the InSAR interferometer pair based on the reference DEM data, the optical reference benchmark and the geometric correction parameters, so as to refine the initial baseline using the elevation correction control points to obtain a target baseline; Based on the geometric correction parameters and the target baseline, performing phase height conversion processing on the unwrapped phase to convert the unwrapped phase into a target digital surface model corresponding to the study area; Extracting elevation correction control points from the InSAR interferometer pair based on the reference DEM data, the optical reference benchmark and the geometric correction parameters, and using the elevation correction control points to refine the initial baseline to obtain a target baseline, including: performing geometric correction on the InSAR interferometer pair according to the geometric correction parameters to obtain an accurate geometric geographic range of the image; extracting elevation correction control points from the InSAR interferometer pair based on the accurate geometric geographic range of the image with reference to the reference DEM data and the optical reference benchmark; screening the elevation correction control points according to the image coherence corresponding to the InSAR interferometer pair to obtain target elevation correction control points; and using the target elevation correction control points to refine the initial baseline to obtain a target baseline; Refining the initial baseline using the target elevation correction control points to obtain a target baseline, including: using a least squares method to fit a baseline refinement function based on the target elevation correction control points, inputting the initial baseline into the baseline refinement function, and obtaining a target baseline output by the baseline refinement function; Based on the geometric correction parameters and the target baseline, the unwrapped phase is subjected to phase height conversion processing to convert the unwrapped phase into a target digital surface model corresponding to the study area, including: using a phase height conversion model, based on the target baseline, the unwrapped phase is subjected to phase height conversion processing to convert the unwrapped phase into an initial digital surface model corresponding to the study area; and using the geometric correction parameters to perform coordinate conversion processing on the initial digital surface model to obtain a target digital surface model corresponding to the study area.

2. The method for generating a digital surface model taking into account both plane and elevation according to claim 1, characterized in that: Combined with the reference DEM data and the optical reference benchmark, the InSAR interferometer pair is subjected to rational polynomial parameter solution processing, control point and tie point automatic extraction processing, and plane adjustment solution processing to obtain geometric correction parameters corresponding to the InSAR interferometer pair, including: Extracting a rigorous imaging model of the InSAR interferometer pair, and performing rational polynomial parameter solving processing on the InSAR interferometer pair through the rigorous imaging model to obtain rational polynomial parameters; Using the rational polynomial parameters and the reference DEM data, pre-ortho-processing is performed on the main image in the InSAR interferometer pair to obtain the initial geometric geographic location of the image of the InSAR interferometer pair; Taking the reference DEM data and the optical reference benchmark as references, and based on the initial geometrical geographic location of the image, automatically extracting control points and connection points of the InSAR interference pair to obtain initial control points and initial connection points; The initial control points and the initial connection points are used to perform plane adjustment processing on the InSAR interferometer pair to obtain geometric correction parameters corresponding to the InSAR interferometer pair.

3. The method for generating a digital surface model taking into account both plane and elevation according to claim 1, characterized in that: Performing baseline calculation processing on the InSAR interferometer pair to obtain an initial baseline corresponding to the InSAR interferometer pair and its corresponding unwrapped phase, including: According to the position, velocity and time information of the InSAR interferometer pair, a position polynomial model and a velocity polynomial model are fitted respectively, so as to determine the satellite position vector corresponding to any position in the image included in the InSAR interferometer pair based on the position polynomial model, and determine the antenna center instantaneous velocity vector corresponding to any position in the image included in the InSAR interferometer pair based on the velocity polynomial model; Based on the satellite position vector and the antenna center instantaneous velocity vector, an initial baseline corresponding to the InSAR interference pair is determined, and an unwrapped phase is extracted based on the initial baseline.

4. A digital surface model generation device that takes both plane and elevation into consideration, characterized in that: include: Data acquisition module, used to obtain InSAR interferometric pairs, reference DEM data and optical reference benchmarks corresponding to the study area; A data processing module is used to combine the reference DEM data and the optical reference benchmark, perform rational polynomial parameter solution processing, automatic extraction processing of control points and connection points, and plane adjustment solution processing on the InSAR interferometer pair, and obtain geometric correction parameters corresponding to the InSAR interferometer pair; and performing baseline calculation processing on the InSAR interference pair to obtain an initial baseline corresponding to the InSAR interference pair and its corresponding unwrapped phase; A baseline refinement module, for extracting elevation correction control points from the InSAR interferometer pair based on the reference DEM data, the optical reference benchmark and the geometric correction parameters, so as to refine the initial baseline using the elevation correction control points to obtain a target baseline; A digital surface model generation module, configured to perform phase height conversion processing on the unwrapped phase based on the geometric correction parameters and the target baseline, so as to convert the unwrapped phase into a target digital surface model corresponding to the study area; The baseline refinement module is specifically used for: performing geometric correction on the InSAR interferometer pair according to the geometric correction parameters to obtain the precise geometric geographic range of the image; taking the reference DEM data and the optical reference benchmark as reference, extracting elevation correction control points from the InSAR interferometer pair based on the precise geometric geographic range of the image; screening the elevation correction control points according to the image coherence corresponding to the InSAR interferometer pair to obtain the target elevation correction control points; and using the target elevation correction control points to refine the initial baseline to obtain the target baseline; The baseline refinement module is specifically used to: use the least square method to fit the baseline refinement function based on the target elevation correction control point, input the initial baseline into the baseline refinement function, and obtain the target baseline output by the baseline refinement function; The digital surface model generation module is specifically used to: perform phase height conversion processing on the unwrapped phase based on the target baseline through a phase height conversion model to convert the unwrapped phase into an initial digital surface model corresponding to the study area; and perform coordinate conversion processing on the initial digital surface model using the geometric correction parameters to obtain a target digital surface model corresponding to the study area.

5. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the method according to any one of claims 1 to 3.

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