SAR geometric distortion identification method based on local incidence angle and virtual terrain change

Abstract

The application discloses a SAR geometric distortion identification method based on local incidence angle and virtual terrain change, and comprises the following steps: extracting radar incidence angle and satellite azimuth angle according to target area SAR data, and calculating radar line-of-sight azimuth angle; obtaining target area DEM data, and calculating slope angle and slope direction, and spatially interpolating radar incidence angle and radar line-of-sight azimuth angle into a DEM grid; calculating local incidence angle according to the radar incidence angle, the radar line-of-sight azimuth angle, the slope angle and the slope direction in the DEM grid; determining four kinds of active geometric distortion information, i.e., perspective contraction, active overlap, resolution enhancement and active shadow, according to the relationship between the local incidence angle and the radar incidence angle; searching for a critical point of an active geometric distortion region, and constructing a virtual terrain pixel by pixel, calculating a virtual terrain slope angle, and searching for a position where the virtual terrain slope angle is equal to the incidence slope angle to determine a passive geometric distortion region; and superimposing the active geometric distortion and the passive geometric distortion to obtain the final geometric distortion.

Description

Technical Field

[0001] This invention pertains to InSAR data processing and disaster monitoring, and particularly relates to a SAR geometric distortion identification method based on local incident angle and virtual terrain changes. Background Technology

[0002] InSAR (Interferometric Synthetic Aperture Radar) technology offers significant advantages over traditional monitoring methods in large-scale surface displacement monitoring (landslide creep, surface subsidence, inter-seismic displacement, fault creep, volcanic expansion and contraction, permafrost thawing, mining subsidence, reservoir bank displacement, etc.), including high spatial resolution, strong historical traceability, wide monitoring range, and low monitoring cost. The effectiveness of SAR-based deformation monitoring depends not only on the sensor type (wavelength: X / C / S / L / P, etc.), acquisition strategy, and processing method, but also on local surface characteristics, including terrain type (plains, hills, mountains), terrain features (slope, aspect), land use type, displacement rate, and the spatiotemporal variability of movement. Currently, spaceborne SAR typically employs side-looking imaging geometry to avoid aliasing of ground target echo signals. However, this can lead to several specific geometric distortions (GD) in SAR images, including foreshortening, layover, enhanced resolution, and shadowing. The degree and type of these distortions depend on the radar incident angle and the slope and aspect of the local terrain; therefore, these distortions often occur in mountainous areas with complex topography. The direct result of SAR geometric distortion is the mixing of pixel signals, which reduces the scattering stability of target points and further affects the accuracy of deformation inversion of temporal feature points in mountainous areas. Therefore, when using InSAR technology for the identification, monitoring, and early warning of deformation hazards in complex terrain, the impact of geometric distortion must be considered. SAR geometric distortions include... Figure 1 As shown.

[0003] In 1990, Kropatsch et al. proposed the LSM (Layover and Shadow Map) method, which can identify both overlay and shadow distortion (including their corresponding active and passive distortions). However, it requires a large number of parameters for calculation, and inaccurate parameters can increase the uncertainty of the results. In 2010, Notti et al. proposed the R-index method, which can effectively identify perspective contraction and active overlay, but cannot obtain passive overlay and shadow information. In 2018, Chen et al. proposed the adjacent gradient method (P-NG), which can identify perspective contraction, active and passive overlay, and active and passive shadows. However, it uses a pixel-by-pixel discrimination method, resulting in slow detection speed for geometric distortion in large areas. In addition, this method does not consider terrain slope correction when identifying active distortion. Therefore, it is evident that several commonly used SAR geometric distortion methods currently exist with their own drawbacks and are difficult to adapt to wide-area, detailed SAR geometric distortion identification. Summary of the Invention

[0004] To overcome the shortcomings of the prior art, the present invention provides a SAR geometric distortion identification method based on local incidence angle and virtual terrain changes. The method first takes into account the slope correction to calculate the local incidence angle and identifies active distortion based on it. Then, it uses the change in terrain slope to detect passive distortion information and finally superimposes to form a complete geometric distortion result.

[0005] According to one aspect of the present invention, a method for identifying SAR geometric distortion based on local incident angle and virtual terrain changes is provided, comprising:

[0006] The radar incident angle and satellite azimuth angle are extracted from the SAR data of the target area, and the radar line-of-sight azimuth angle is calculated based on the satellite azimuth angle.

[0007] Acquire DEM data of the target area, calculate the slope angle and aspect based on the terrain information of the DEM data, and spatially interpolate the radar incident angle and radar line-of-sight azimuth angle into the DEM grid.

[0008] Calculate the local angle of incidence based on the radar incident angle, radar line-of-sight azimuth, slope angle, and slope aspect in the DEM grid;

[0009] Based on the relationship between the local incident angle and the radar incident angle, four types of active geometric distortion information are determined: perspective shrinkage, active overlay, resolution enhancement, and active shading, and then the active geometric distortion region is determined.

[0010] Search for the critical points of the active geometric distortion region, construct virtual terrain pixel by pixel, calculate the slope angle of the virtual terrain, and find the position where it is equal to the incident slope angle by the change of the virtual terrain slope angle to determine the passive geometric distortion region.

[0011] The active geometric distortion region and the passive geometric distortion region are superimposed to obtain the final geometric distortion region.

[0012] As a further technical solution, the radar incident angle and satellite azimuth angle are extracted based on the SAR data of the target area, and the following are also included:

[0013] The data coverage area is extracted from the SAR data of the target area, and the DEM data range of the target area is determined based on the extracted data coverage area.

[0014] As a further technical solution, the local incidence angle is calculated based on the radar incidence angle, radar line-of-sight azimuth angle, slope angle, and slope aspect in the DEM grid. The expression is as follows:

[0015] ,

[0016] in, For local incident angle, The radar incident angle, This is the radar line-of-sight azimuth angle. The slope angle, It is a slope.

[0017] As a further technical solution, four types of active geometric distortion information—perspective shrinkage, active overlay, resolution enhancement, and active shading—are determined based on the relationship between the local incident angle and the radar incident angle.

[0018] At this time, perspective contraction occurs;

[0019] At this time, it is an active overlapping;

[0020] At that time, the resolution was enhanced;

[0021] At that time, it is an active shadow.

[0022] As a further technical solution, calculate the virtual terrain slope angle. for:

[0023] ,

[0024] in, and These are the height and length of the virtual terrain portion, respectively.

[0025] As a further technical solution, the passive geometric distortion region is determined by finding the location where the virtual terrain slope angle is equal to the incident slope angle through changes in the virtual terrain slope angle, including:

[0026] Search for the critical point of active overlay distortion and calculate the virtual terrain slope angle using virtual terrain changes. Determine the slope angle of the virtual terrain With the angle of incidence The relationship is used to search for near-range passive overlay and far-range passive overlay on both the near and far sides respectively;

[0027] Search for the critical point of active shadow distortion and calculate the virtual terrain slope angle using virtual terrain changes. Determine the slope angle of the virtual terrain With the angle of incidence The relationship is such that the passive shadow is searched for on the far side.

[0028] As a further technical solution, the method also includes:

[0029] When searching for near-range passive overlap, the search starts from the near-range critical point of active overlap and proceeds in the opposite direction of the radar line of sight towards the near-range end. The basis for determining near-range passive overlap at this point is... ,in , To actively mask the radar incident angle at the long-range critical point; when At that time, the critical point of near-range passive overlay was found;

[0030] When searching for long-range passive overlay, the search proceeds from the long-range critical point of active overlay along the radar line of sight towards the far end. The basis for determining long-range passive overlay at this time is: ,in , To actively mask the radar incident angle at the near-range critical point; when At that time, the critical point of long-distance passive overlay was found.

[0031] As a further technical solution, the method also includes:

[0032] When searching for passive shadow geometric distortion, first find the active shadow's far-distance critical point on the far side of the radar line of sight. Then, starting from the active shadow's far-distance critical point, continue searching for the passive shadow's zero point along the radar line of sight. Among them, the pixels traversed between the active shadow's far-distance critical point and the passive shadow's zero point are all passive shadows.

[0033] According to one aspect of the present invention, a SAR geometric distortion identification system based on local incident angle and virtual terrain changes is provided, for implementing the SAR geometric distortion identification method based on local incident angle and virtual terrain changes, comprising:

[0034] The first main module is used to extract the radar incident angle and satellite azimuth angle based on the SAR data of the target area, and to calculate the radar line-of-sight azimuth angle based on the satellite azimuth angle.

[0035] The second main module is used to acquire DEM data of the target area, calculate the slope angle and aspect based on the terrain information of the DEM data, and spatially interpolate the radar incident angle and radar line-of-sight azimuth angle into the DEM grid.

[0036] The third main module is used to calculate the local incident angle based on the radar incident angle, radar line-of-sight azimuth angle, slope angle and slope aspect in the DEM grid.

[0037] The fourth main module is used to determine four types of active geometric distortion information—perspective shrinkage, active overlay, resolution enhancement, and active shading—based on the relationship between the local incident angle and the radar incident angle, and then to determine the active geometric distortion region.

[0038] The fifth main module is used to search for the critical point of the active geometric distortion region, construct virtual terrain pixel by pixel, calculate the slope angle of the virtual terrain, and find the position where it is equal to the incident slope angle by the change of the virtual terrain slope angle to determine the passive geometric distortion region.

[0039] The sixth main module is used to superimpose the active geometric distortion region and the passive geometric distortion region to obtain the final geometric distortion region.

[0040] According to one aspect of the present invention, a non-transitory computer-readable storage medium is provided, the non-transitory computer-readable storage medium storing computer instructions that cause the computer to execute the SAR geometric distortion identification method based on local incident angle and virtual terrain changes.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0042] 1. This invention's method considers slope angle correction for local incidence to more accurately identify active geometric distortions. It also proposes the concept of virtual terrain change, enabling comprehensive and rapid identification of geometric distortion information in target areas. It can serve for InSAR deformation inversion quality assessment in complex terrain scenarios and rapid data availability assessment in disaster emergency scenarios. Furthermore, it can generate a data quality mask using the identified detailed geometric distortion information to remove large errors in severely distorted areas. Additionally, it can be used for geometric distortion information estimation of target areas before SAR data processing, serving as a basis for selecting superior SAR observation data and reducing the time cost of repeated data testing. This has significant advantages in rapid disaster emergency service scenarios.

[0043] 2. This invention proposes the concept of Virtual Terrain Change (VTC) in passive geometric distortion detection, defining the virtual terrain as the portion between the line connecting the active distortion critical point (S) to the point to be detected (P) and the real terrain. This SAR geometric distortion identification method based on local incidence angle and virtual terrain change is called LiVTC (Local-incidence angle & Virtual Terrain Change). This method transforms the complex geometric relationships in the SAR geometric distortion identification process into comparing the magnitudes of the local incidence angle and the virtual terrain slope with the radar incidence angle. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of SAR geometric distortion in existing technologies.

[0046] Figure 2 This is a schematic diagram of the SAR geometric distortion identification method based on local incident angle and virtual terrain changes provided in an embodiment of the present invention.

[0047] Figure 3 This is a schematic diagram of local incident angle and active distortion identification considering slope angle correction provided in an embodiment of the present invention.

[0048] Figure 4 Figures a and b in the figure are schematic diagrams of passive shadow recognition provided in the embodiments of the present invention.

[0049] Figure 5 Figures a and b in the figure are schematic diagrams of near-range / far-range passive overlay recognition provided in the embodiments of the present invention. Detailed Implementation

[0050] To address the limitations of commonly used SAR geometric distortion methods in identifying wide-area, detailed SAR geometric distortions, this invention provides a SAR geometric distortion identification method based on local incident angle and virtual terrain variation. By considering slope angle correction in the local incident angle, it identifies fine-grained active geometric distortion information, providing more accurate prior information for passive geometric distortion detection. Furthermore, a novel Virtual Terrain Variation (VTC) concept is proposed for SAR passive geometric distortion identification, and a new geometric distortion identification method, LiVTC, is constructed based on the local incident angle and VTC. This method can comprehensively and meticulously identify perspective contraction, active overlay, near-range passive overlay, far-range passive overlay, resolution enhancement, active shading, and passive shading distortion information, and significantly simplifies the complex geometric relationships in the identification process, making the method easier to use.

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. In addition, the technical features of the various embodiments or individual embodiments provided by the present invention can be arbitrarily combined to form new technical solutions. Such combinations are not bound by the order of steps and / or structural composition patterns, but must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0052] This invention provides a SAR geometric distortion identification method based on local incident angle and virtual terrain changes, such as... Figure 2 As shown, it includes the following steps:

[0053] Step 1: Extract the radar incident angle based on the regional SAR data. ), satellite azimuth ( ) and data coverage area, and calculate the radar line-of-sight azimuth angle based on the satellite azimuth angle ( ):

[0054] ;

[0055] Step 2: Determine the regional DEM data range based on the data range, and acquire high-resolution DEM data for the target area. Calculate the slope and aspect based on the DEM terrain information, and set the radar incident angle ( ). ) and line of sight azimuth ( Spatial interpolation into the DEM grid;

[0056] Step 3, based on the radar incident angle in the DEM grid ( ), line of sight azimuth ( ),slope( ) and slope aspect ( ) Calculate the local incident angle ( ):

[0057] ;

[0058] Step 4: Determine four types of geometric distortion information—perspective shrinkage, active overlay, resolution enhancement, and active shading—based on the relationship between the local incident angle and the radar incident angle.

[0059] Step 5: Search for the critical points of the active distortion region, construct virtual terrain pixel by pixel, and calculate the slope of the virtual terrain. The passive geometric distortion region is determined by finding the position (passive distortion zero point) where the slope angle of the virtual terrain is equal to the incident slope angle (the complementary angle of the radar incident angle at the active distortion zero point).

[0060] ,

[0061] in, and These are the height and length of the virtual terrain portion, respectively.

[0062] Step 6: Superimpose the active geometric distortion results and the passive geometric distortion results to obtain the final geometric distortion result.

[0063] Figure 3 A schematic diagram of local incident angle and active distortion identification considering slope angle correction is presented. The active geometric distortion types corresponding to the relationship between local incident angle and radar incident angle are shown in Table 1.

[0064] Table 1. Types of Active Geometric Distortions Corresponding to the Relationship Between Local Incident Angle and Radar Incident Angle

[0065] .

[0066] Figure 4 Figures a and b in the diagram illustrate a method for identifying SAR passive shadows based on Virtual Terrain Change (VTC). Searching for passive shadow geometric distortions requires first identifying the active shadow's far-field critical point on the radar line-of-sight side. ), and then from the critical point ( Starting from this point, continue searching for the passive shadow boundary point at a distance along the radar line of sight. ), then the active shadow critical point ( From the passive shadow boundary point ( The pixels traversed between () are all passive shadows. Figure 4 In Figure a, passive shadows appear at the intersection of the radar line of sight and the distant ground surface at the near-field threshold (S) of active shadows. The intersection point between these two points is the passive shadow boundary point. (Combined with...) Figure 4 In Figure b, the virtual terrain represents the current search point. ) and the active shadow near-field threshold (S) and the active shadow far-field threshold ( The slope of the virtual terrain, formed by the portion of the terrain formed by the virtual terrain, can be calculated as follows:

[0067] ,

[0068] In the formula, These are the active shadow proximity threshold (S) and the current search point, respectively. Elevation, The difference in elevation between these two points; These are the active shadow proximity threshold (S) and the current search point, respectively. Distance along the line of sight, This represents the distance difference between these two points.

[0069] So, by comparing the slope of the virtual terrain ( The intersection of radar line of sight and distant ground surface at the near-field threshold (S) of active shadowing. The slope of () () That is, the incident angle slope), which can quickly determine whether the current search point is a passive shadow distortion region ( Passive shadow, continue searching for the next pixel; Passive shadow boundary point detected; search ends. The radar incident angle is at the near-field critical point (S) of active shadowing.

[0070] Figure 5 Figures a and b in the diagram illustrate a method for identifying near / far-range passive overlay of SAR based on Virtual Terrain Change (VTC). Combined with... Figure 5 As shown in Figure a, passive overlay is divided into near-range passive overlay and far-range passive overlay, which are located on the near / far side of the active overlay distortion, respectively. Therefore, it is necessary to search along two directions separately. (Combined with...) Figure 5 As shown in Figure b, when searching for near-range passive overlay, it is necessary to use active overlay near-range critical points ( Starting from [a certain point], the search proceeds in the opposite direction of the radar line of sight towards the near end, and the corresponding virtual terrain slope is calculated in the same way as above. The basis for determining this as near-range passive overlay is: ,in , Actively overlaying distant critical points The radar incident angle at the location; when At that time, the critical point of near-range passive overlay was found. The search ends. When searching for long-range passive overlay, the search should start from the long-range critical point of active overlay and proceed along the radar line of sight towards the far end. The criteria for determining long-range passive overlay at this point are: ,in , Actively overlaying near-critical point The radar incident angle at the location; when At that time, the critical point of long-distance passive overlay was found. ), end the search.

[0071] The following example, using a local area of ​​a province, illustrates the processing procedure and effect of the SAR geometric distortion identification method based on local incident angle and virtual terrain changes proposed in this invention. The specific steps are as follows:

[0072] (1) Query the SAR data observation geometry information of a certain town in a certain province, determine the radar incident angle (ascending orbit: ~40°; descending orbit: ~39.6°) and satellite azimuth angle (ascending orbit: ~349.5°; descending orbit: ~190.5°), and calculate the radar line-of-sight azimuth angle (ascending orbit: ~79.5°; descending orbit: ~280.5°) based on the satellite azimuth angle information.

[0073] (2) Download the Copernicus GLO-30 digital elevation model (DEM) of the target area, calculate the slope angle and slope aspect information pixel by pixel based on the DEM topographic information, and interpolate the SAR observation geometric information (radar incident angle, line of sight azimuth angle) to the DEM grid.

[0074] (3) Based on the radar incident angle of the DEM grid ( ), line of sight azimuth ( ), slope angle ( ) and slope aspect ( Calculate the local incident angle;

[0075] (4) Determine four types of geometric distortion information—perspective shrinkage, active overlay, resolution enhancement, and active shading—based on the relationship between the local incident angle and the radar incident angle;

[0076] (5) Search for the critical point of active overlay distortion, and use the virtual terrain change method to calculate the virtual terrain slope angle, determine its relationship with the incident slope angle, and search for near passive overlay and far passive overlay on both the near and far sides respectively.

[0077] (6) Search for the critical point of active shadow distortion, and use the virtual terrain change method to calculate the virtual terrain slope angle, determine its relationship with the incident slope angle, and search for passive shadows to the far side;

[0078] (7) Superimpose the active geometric distortion and passive geometric distortion calculated in (4), (5) and (6) to generate a complete geometric distortion map.

[0079] The implementation of the various embodiments of the present invention is based on programmed processing by a device with processor functionality. Therefore, in practical engineering, the technical solutions and functions of the various embodiments of the present invention are encapsulated into various modules. Based on this reality, and building upon the above embodiments, the embodiments of the present invention provide a SAR geometric distortion identification system based on local incident angle and virtual terrain changes. This system is used to execute the SAR geometric distortion identification method based on local incident angle and virtual terrain changes in the above method embodiments.

[0080] The system comprises: a first main module for extracting radar incident angle and satellite azimuth angle from SAR data of the target area, and calculating radar line-of-sight azimuth angle based on satellite azimuth angle; a second main module for acquiring DEM data of the target area, calculating slope angle and aspect based on terrain information of the DEM data, and spatially interpolating radar incident angle and radar line-of-sight azimuth angle into the DEM grid; a third main module for calculating local incident angle based on radar incident angle, radar line-of-sight azimuth angle, slope angle, and aspect in the DEM grid; a fourth main module for determining four types of active geometric distortion information—perspective shrinkage, active overlay, resolution enhancement, and active shading—based on the relationship between local incident angle and radar incident angle, thereby determining active geometric distortion regions; a fifth main module for searching the critical points of active geometric distortion regions, constructing virtual terrain pixel by pixel, calculating virtual terrain slope angle, and finding the position where the virtual terrain slope angle is equal to the incident slope angle to determine passive geometric distortion regions; and a sixth main module for superimposing active and passive geometric distortion regions to obtain the final geometric distortion region.

[0081] This invention provides a SAR geometric distortion identification system based on local incidence angle and virtual terrain changes. Addressing the problem that current SAR geometric distortion methods are difficult to adapt to wide-area and detailed SAR geometric distortion identification, this system employs several modules mentioned above. It first calculates the local incidence angle by taking slope correction into account and identifies active distortion based on this angle. Then, it uses changes in terrain slope to detect passive distortion information and finally superimposes the results to form a complete geometric distortion result.

[0082] It should be noted that the system embodiments provided by the present invention are used not only to implement the methods in the above method embodiments, but also to implement the methods in other method embodiments provided by the present invention. The only difference is that corresponding functional modules are set. The principle is basically the same as that of the above system embodiments provided by the present invention. As long as those skilled in the art can improve the modules in the above system embodiments by referring to the specific technical solutions in other method embodiments and combining technical features to obtain corresponding technical means and technical solutions composed of these technical means, on the basis of the above system embodiments, and on the premise of ensuring the practicality of the technical solutions, they can obtain corresponding system-like embodiments for implementing the methods in other method-like embodiments.

[0083] Based on the same inventive concept as the foregoing embodiments, this embodiment of the invention also provides a non-transitory computer-readable storage medium storing computer instructions that cause the computer to execute the SAR geometric distortion identification method based on local incident angle and virtual terrain changes.

[0084] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0085] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0086] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0087] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0088] In summary, the LiVTC method proposed in this invention takes into account the slope angle correction of local incident angle to more accurately identify active geometric distortions. It also proposes the concept of virtual terrain change, enabling comprehensive and rapid identification of geometric distortion information in the target area. Table 2 shows a comparison of the SAR geometric distortion identification capabilities of the LiVTC method described in this invention with three other typical and commonly used methods.

[0089] Table 2 Comparison of SAR geometric distortion recognition capabilities between the LiVTC method and three other typical and commonly used methods

[0090] .

[0091] The terms “comprising” and “having”, and any variations thereof, in the specification, claims, and accompanying drawings of this invention are intended to cover a non-exclusive inclusion, such as a process, method, system, product, or apparatus that includes a series of steps or units, not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0092] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A SAR geometric distortion identification method based on local incident angle and virtual terrain changes, characterized in that, include: The radar incident angle and satellite azimuth angle are extracted from the SAR data of the target area, and the radar line-of-sight azimuth angle is calculated based on the satellite azimuth angle. Acquire DEM data of the target area, calculate the slope angle and aspect based on the terrain information of the DEM data, and spatially interpolate the radar incident angle and radar line-of-sight azimuth angle into the DEM grid. Calculate the local angle of incidence based on the radar incident angle, radar line-of-sight azimuth, slope angle, and slope aspect in the DEM grid; Based on the relationship between the local incident angle and the radar incident angle, four types of active geometric distortion information are determined: perspective shrinkage, active overlay, resolution enhancement, and active shading, and then the active geometric distortion region is determined. Search for the critical points of the active geometric distortion region, construct virtual terrain pixel by pixel, calculate the slope angle of the virtual terrain, and find the position where it is equal to the incident slope angle by the change of the virtual terrain slope angle to determine the passive geometric distortion region. The active geometric distortion region and the passive geometric distortion region are superimposed to obtain the final geometric distortion region.

2. The SAR geometric distortion identification method based on local incident angle and virtual terrain changes according to claim 1, characterized in that, Based on the SAR data of the target area, the radar incident angle and satellite azimuth angle are extracted, including: The data coverage area is extracted from the SAR data of the target area, and the DEM data range of the target area is determined based on the extracted data coverage area.

3. The SAR geometric distortion identification method based on local incident angle and virtual terrain changes according to claim 1, characterized in that, The local incidence angle is calculated based on the radar incidence angle, radar line-of-sight azimuth angle, slope angle, and slope aspect in the DEM grid. The expression is as follows: ， in, For local incident angle, The radar incident angle, This is the radar line-of-sight azimuth angle. The slope angle, It is a slope.

4. The SAR geometric distortion identification method based on local incident angle and virtual terrain changes according to claim 3, characterized in that, Based on the relationship between the local incident angle and the radar incident angle, four types of active geometric distortion information are determined: perspective shrinkage, active overlay, resolution enhancement, and active shading. At this time, perspective contraction occurs; At this time, it is an active overlapping; At that time, the resolution was enhanced; At that time, it is an active shadow.

5. The SAR geometric distortion identification method based on local incident angle and virtual terrain changes according to claim 1, characterized in that, Calculate the slope angle of the virtual terrain for: ， in, and These are the height and length of the virtual terrain portion, respectively.

6. The SAR geometric distortion identification method based on local incident angle and virtual terrain changes according to claim 5, characterized in that, By finding locations where the slope angle of the virtual terrain equals the incident slope angle, the passive geometric distortion region can be determined, including: Search for the critical point of active overlay distortion and calculate the virtual terrain slope angle using virtual terrain changes. Determine the slope angle of the virtual terrain With the angle of incidence The relationship is used to search for near-range passive overlay and far-range passive overlay on both the near and far sides respectively; Search for the critical point of active shadow distortion and calculate the virtual terrain slope angle using virtual terrain changes. Determine the slope angle of the virtual terrain With the angle of incidence The relationship is such that the passive shadow is searched for on the far side.

7. The SAR geometric distortion identification method based on local incident angle and virtual terrain changes according to claim 6, characterized in that, The method further includes: When searching for near-range passive overlap, the search starts from the near-range critical point of active overlap and proceeds in the opposite direction of the radar line of sight towards the near-range end. The basis for determining near-range passive overlap at this point is... ,in , To actively mask the radar incident angle at the long-range critical point; when At that time, the critical point of near-range passive overlay was found; When searching for long-range passive overlay, the search proceeds from the long-range critical point of active overlay along the radar line of sight towards the far end. The basis for determining long-range passive overlay at this time is: ,in , To actively mask the radar incident angle at the near-range critical point; when At that time, the critical point of long-distance passive overlay was found.

8. The SAR geometric distortion identification method based on local incident angle and virtual terrain changes according to claim 6, characterized in that, The method further includes: When searching for passive shadow geometric distortion, first find the active shadow's far-distance critical point on the far side of the radar line of sight. Then, starting from the active shadow's far-distance critical point, continue searching for the passive shadow's zero point along the radar line of sight. Among them, the pixels traversed between the active shadow's far-distance critical point and the passive shadow's zero point are all passive shadows.

9. A SAR geometric distortion identification system based on local incident angle and virtual terrain changes, used to implement the SAR geometric distortion identification method based on local incident angle and virtual terrain changes as described in any one of claims 1 to 8, characterized in that, include: The first main module is used to extract the radar incident angle and satellite azimuth angle based on the SAR data of the target area, and to calculate the radar line-of-sight azimuth angle based on the satellite azimuth angle. The second main module is used to acquire DEM data of the target area, calculate the slope angle and aspect based on the terrain information of the DEM data, and spatially interpolate the radar incident angle and radar line-of-sight azimuth angle into the DEM grid. The third main module is used to calculate the local incident angle based on the radar incident angle, radar line-of-sight azimuth angle, slope angle and slope aspect in the DEM grid. The fourth main module is used to determine four types of active geometric distortion information—perspective shrinkage, active overlay, resolution enhancement, and active shading—based on the relationship between the local incident angle and the radar incident angle, and then to determine the active geometric distortion region. The fifth main module is used to search for the critical point of the active geometric distortion region, construct virtual terrain pixel by pixel, calculate the slope angle of the virtual terrain, and find the position where it is equal to the incident slope angle by the change of the virtual terrain slope angle to determine the passive geometric distortion region. The sixth main module is used to superimpose the active geometric distortion region and the passive geometric distortion region to obtain the final geometric distortion region.

10. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions that cause the computer to execute the SAR geometric distortion identification method based on local incident angle and virtual terrain changes as described in any one of claims 1 to 8.

Images