Point selection method and system for dual polarization of time sequence InSAR (Interferometric Synthetic Aperture Radar) image

Abstract

The invention relates to the field of microwave remote sensing interferometry, in particular to a time sequence InSAR image dual polarization point selection method and system. Comprising the following steps: acquiring a dual-polarization image of a monitoring area, and constructing a polarization basis transformation equation according to a decomposition result of the dual-polarization image; obtaining parameter distribution of the dual-polarization image according to the polarization basis transformation equation, and setting an optimization initial value according to the parameter distribution of the dual-polarization image; an optimal polarization combination is generated according to the optimization initial value and a preset optimization algorithm model, and surface deformation points are obtained according to PSInSAR technology processing of the optimal polarization combination; and the deformation points are densest on the premise of ensuring the precision of the deformation points. The optimal polarization combination related to the point selection mode is obtained through the optimization model, more deformation points can be extracted in the whole monitoring area, the deformation points are densest on the premise that the precision of the deformation points is guaranteed, the precision of the rates of the single-polarization (HH polarization) and OPT polarization deformation points is verified through the nearest neighbor point method, and the accuracy of the rate of the single-polarization (HH polarization) and OPT polarization deformation points is verified. And the density of deformation points is compared through point number distribution.

Description

Technical Field

[0001] This application relates to the field of microwave remote sensing interferometry, and in particular to a point selection method and system for dual polarization of time-series InSAR images. Background Technology

[0002] Synthetic Aperture Radar (SAR) is an active imaging sensor with all-weather, 24 / 7 data acquisition capabilities, finding wide application in fields such as geological disaster assessment, land cover classification, and ship identification. Currently, multi-polarization, multi-band SAR data is gradually becoming the mainstream in the market, placing higher demands on research directions such as SAR imaging and interferometric SAR.

[0003] Currently, single-polarization SAR image point selection suffers from problems such as a small number of polarimetric points (PS points) and low quality reliability, directly resulting in limited usable information and large errors in deformation results. While there are various methods for selecting PS points, such as the intensity threshold method, amplitude deviation index method, and coherence-based point selection method, all are based on single-polarization data and cannot utilize more polarization information to obtain more PS points. Summary of the Invention

[0004] The purpose of this application is to provide a method and system for selecting points using time-series InSAR image dual polarization in order to solve the above-mentioned technical problems, thereby obtaining more deformation information of the monitoring area and improving the accuracy of deformation assessment results.

[0005] In some embodiments of this application, by constructing polarization basis transformation equations and obtaining the optimal polarization combination for point selection through an optimization model, more deformation points can be extracted in the entire monitoring area. Under the premise of ensuring the accuracy of deformation points, the deformation points are made the most dense. Accuracy verification relies on the comparison of the rates of the nearest deformation points of single polarization (HH polarization) and OPT polarization. The most dense deformation is achieved by comparing the distribution of the number of points.

[0006] In some embodiments of this application, the initial value for optimization is set according to the distribution of copolarized image parameters, which ensures that the optimization process quickly converges to the vicinity of the global optimum, avoids getting trapped in local optima and wasting computational resources, and saves computation time.

[0007] In some embodiments of this application, a point selection method for dual polarization of temporal InSAR images is provided, including:

[0008] Collect dual-polarization images of the monitoring area and construct polarization basis transformation equations based on the decomposition results of the dual-polarization images; The parameter distribution of the same polarization image is obtained according to the polarization basis transformation equation, and the initial value for optimization is set according to the parameter distribution of the same polarization image. The optimal polarization combination is generated based on the initial optimization value and the preset optimization algorithm model. The surface deformation points are obtained by PSInSAR technology based on the optimal polarization combination.

[0009] In some embodiments of this application, the construction of the polarization basis transformation equation includes: The polarization scattering matrix [S] is constructed based on the linear relationship between the polarization terms of the radar transmitted wave and the target scattered echo; ; in, It is an electromagnetic wave. It is the natural logarithm. For the antenna to transmit waves, For the target scattered wave, The distance between the radar receiving antenna and the scattering target. and It is a homopolar combination; and It is a cross-polarization combination. Indicates the electromagnetic wave coefficient; Define the Pauli basis for the polarization scattering matrix [S]: ; in, These represent different scattering mechanisms. Let these represent the power of the scattering mechanism, respectively. According to the reciprocity theorem and the monostation system, i.e. ; The scattering matrix [S] is vectorized using the pauli basis to generate the polarization vector k.

[0010] In some embodiments of this application, the construction of the polarization basis transformation equation further includes: Obtain the projection vector ; Based on the polarization vector k and the projection vector Set the scattering coefficient μ; ; Indicates the conjugate operation; The polarization basis transformation equation is constructed based on the scattering coefficient μ.

[0011] In some embodiments of this application, the generation of the polarization vector k includes: Establish a dual-polarization combination of VV and VH, and generate vector k based on the polarization combination. VV / VH ; ; Establish a dual-polarization combination of HH and HV, and generate vector k based on the polarization combination. HH / VH ; ; Establish a dual-polarization combination of HH and VV, and generate vector k based on the polarization combination.HH / VV; .

[0012] In some embodiments of this application, the parameter distribution of co-polarized images is obtained according to the polarization basis transformation equation, including: Generate amplitude deviation under single-polarization conditions; Establish the functional relationship between the amplitude deviation exponent and the Pauli basis: ; The parameter distribution of the same polarization image was calculated based on the single threshold method.

[0013] In some embodiments of this application, a point selection system for time-series InSAR image dual polarization is provided, including: The monitoring unit is used to acquire dual-polarization images of the monitoring area; The central control unit includes: The first processing module is used to construct polarization basis transformation equations based on the decomposition results of dual-polarization images; The second processing module is used to obtain the parameter distribution of the same polarization image according to the polarization basis transformation equation, and to set the initial value for optimization according to the parameter distribution of the same polarization image. The third processing module is used to generate the optimal polarization combination based on the initial optimization value and the preset optimization algorithm model, and to obtain the surface deformation points by processing the optimal polarization combination using PSInSAR technology.

[0014] In some embodiments of this application, the first processing module is configured to: The polarization scattering matrix [S] is constructed based on the linear relationship between the polarization terms of the radar transmitted wave and the target scattered echo; ; in, It is an electromagnetic wave. It is the natural logarithm. For the antenna to transmit waves, For the target scattered wave, The distance between the radar receiving antenna and the scattering target. and It is a homopolar combination; and It is a cross-polarization combination. Indicates the electromagnetic wave coefficient; Define the Pauli basis for the polarization scattering matrix [S]: ; in, These represent different scattering mechanisms. Let these represent the power of the scattering mechanism, respectively. According to the reciprocity theorem and the monostation system, i.e. ; The scattering matrix [S] is vectorized using the pauli basis to generate the polarization vector k; Obtain the projection vector ; Based on the polarization vector k and the projection vector Set the scattering coefficient μ; ; Indicates the conjugate operation; The polarization basis transformation equation is constructed based on the scattering coefficient μ.

[0015] In some embodiments of this application, the first processing module is further configured to: Establish a dual-polarization combination of VV and VH, and generate vector k based on the polarization combination. VV / VH ; ; Establish a dual-polarization combination of HH and HV, and generate vector k based on the polarization combination. HH / VH ; ; Establish a dual-polarization combination of HH and VV, and generate vector k based on the polarization combination. HH / VV; .

[0016] In some embodiments of this application, the second processing module is further configured to: Generate amplitude deviation under single-polarization conditions; Establish the functional relationship between the amplitude deviation exponent and the Pauli basis: ; The parameter distribution of the same polarization image was calculated based on the single threshold method.

[0017] Compared with the prior art, the point selection method and system for dual polarization of temporal InSAR images disclosed in this application have the following advantages: In some embodiments of this application, by constructing polarization basis transformation equations and obtaining the optimal polarization combination for point selection through an optimization model, more deformation points can be extracted in the entire monitoring area. Under the premise of ensuring the accuracy of deformation points, the deformation points are made as dense as possible. The accuracy verification relies on the comparison of the rates of the nearest deformation points of single polarization (HH polarization) and OPT polarization. The densest deformation is achieved through the point number distribution optimization algorithm.

[0018] In some embodiments of this application, the initial value for optimization is set according to the distribution of the same polarization image parameters, which ensures that the optimization process quickly converges to the vicinity of the physically meaningful global optimal solution, avoiding getting trapped in local optima or wasting computational resources, and saving computation time. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a point selection method for time-series InSAR image dual polarization in a preferred embodiment of this application.

[0020] Figure 2 This is a flowchart of the SA algorithm in a preferred embodiment of this application. Detailed Implementation

[0021] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but are not intended to limit the scope of this application.

[0022] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0023] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0024] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0025] like Figures 1-2 As shown, a preferred embodiment of this application provides a point selection method for dual polarization of temporal InSAR images, comprising: S101: Acquire dual-polarization images of the monitoring area and construct polarization basis transformation equations based on the decomposition results of the dual-polarization images; S102: Obtain the parameter distribution of the same polarization image according to the polarization basis transformation equation, and set the initial value for optimization according to the parameter distribution of the same polarization image; S103: Generate the optimal polarization combination based on the initial optimization value and the preset optimization algorithm model, and obtain the surface deformation points by processing the PSInSAR technology based on the optimal polarization combination.

[0026] Specifically, dual-polarization SAR images of high-altitude areas in the monitoring region are selected, and polarization basis transformation equations are established through pauli decomposition.

[0027] Specifically, the permanent scatterer point density of images with different polarization modes varies greatly, and the information comparison between co-polarization (HH, VV) and cross-polarization (HV, VH) significantly increases the number of deformation points. The parameter distribution of the co-polarization image is calculated using the single threshold method.

[0028] Specifically, the threshold of the single threshold method is set according to historical parameters, and the same polarization image with the largest pixel value amplitude deviation index is used as the initial value for the optimization algorithm.

[0029] Specifically, the parameters and gradients of the optimization algorithm are set using parameter distribution, and then the local optimum is optimized to the global optimum through iteration of the polarization basis equation. The optimal polarization combination is selected based on the global optimum.

[0030] Specifically, surface deformation was obtained by processing optimal polarization composite images using the PSInSAR workflow, and the reliability of the polarization-optimal deformation monitoring results was verified using leveling points. Comparing the PSInSAR workflow results of HH and HV polarization, the number of deformation points increased significantly in areas with high and low coherence.

[0031] Specifically, the preset optimization model sets corresponding optimization directions based on different categories of the monitored area, thereby improving optimization efficiency and saving computation time.

[0032] It is understood that in the above embodiments, setting the initial value for optimization based on the distribution of co-polarized image parameters ensures that the optimization process quickly converges to the vicinity of the physically meaningful global optimum, avoiding getting trapped in local optima or wasting computational resources, and saving computation time.

[0033] In a preferred embodiment of this application, constructing the polarization basis transformation equation includes: The polarization scattering matrix [S] is constructed based on the linear relationship between the polarization terms of the radar transmitted wave and the target scattered echo; ; in, It is an electromagnetic wave. It is the natural logarithm. For the antenna to transmit waves, For the target scattered wave, The distance between the radar receiving antenna and the scattering target. and It is a homopolar combination; and It is a cross-polarization combination. Indicates the electromagnetic wave coefficient; Define the Pauli basis for the polarization scattering matrix [S]: ; in, These represent different scattering mechanisms. Let these represent the power of the scattering mechanism, respectively. According to the reciprocity theorem and the monostation system, i.e. ; The scattering matrix [S] is vectorized using the pauli basis to generate the polarization vector k.

[0034] Specifically, constructing the polarization basis transformation equations also includes: Obtain the projection vector ; Based on the polarization vector k and the projection vector Set the scattering coefficient μ; ; Indicates the conjugate operation; The polarization basis transformation equation is constructed based on the scattering coefficient μ.

[0035] Specifically, the expression for is as follows: In the formula: The Pauli parameters represent different scattering mechanisms. Conditions under dual polarization. The third vector does not need to be represented, let as follows: In the formula: Indicates the pauli parameter; Specifically, in the process of transitioning from full polarization to dual polarization, the four-parameter problem is transformed into two parameters, which reduces the amount of computation compared to full polarization optimization.

[0036] Establish a dual-polarization combination of VV and VH, and generate vector k based on the polarization combination. VV / VH ; ; Establish a dual-polarization combination of HH and HV, and generate vector k based on the polarization combination. HH / VH ; ; Establish a dual-polarization combination of HH and VV, and generate vector k based on the polarization combination. HH / VV; .

[0037] It is understandable that in the above embodiments, by constructing polarization basis transformation equations and obtaining the optimal polarization combination for point selection through optimization models, more deformation points can be extracted in the entire monitoring area. Under the premise of ensuring the accuracy of deformation points, the deformation points are made the most dense. The accuracy verification relies on the comparison of the rates of the nearest deformation points of single polarization (HH polarization) and OPT polarization. The most dense deformation is achieved by comparing the distribution of the number of points.

[0038] In a preferred embodiment of this application, obtaining the parameter distribution of a co-polarized image based on the polarization basis transformation equation includes: Generate amplitude deviation under single-polarization conditions; Establish the functional relationship between the amplitude deviation exponent and the Pauli basis: ; The parameter distribution of the same polarization image was calculated based on the single threshold method.

[0039] Specifically, targets with smaller ADI values ​​are known to have better temporal stability. A smaller ADI allows for the acquisition of more ground deformation information through temporal InSAR technology. The SA algorithm is used to find the global optimum. As the annealing temperature decreases, the optimal solution in the SA algorithm tends to stabilize. When a solution gets trapped in a local optimum, according to the Monte Carlo criterion, a probability greater than a random number will be used to accept a solution worse than the current optimal solution, thus escaping the local optimum with a certain probability. The mathematical expression for probability P is given.

[0040]

[0041] In the formula: For probability, These are the old and new interpretations, respectively. and These are the annealing coefficient and the initial temperature, respectively. A probability less than 0.03 indicates that no new solutions will be accepted. and Since the product is greater than 0.15, the value range of K is (0,1). The maximum value is 0.98.

[0042] If the pixel's ADI passes through If no new solution is accepted in each iteration, then it is called... To stabilize the number of cycles and obtain the initial value for the SA algorithm, each pixel of the HH polarization image is set to the initial value of the dual-polarization SA algorithm. As shown in Table 1, the ADI of over 99% of the pixels in the HH polarization image is distributed between 0.2 and 0.8, and the initial temperature is approximately 0.6.

[0043] Table 1. ADI distribution results for HH polarization

[0044] Therefore, five sets of experiments were set with initial temperatures of 0.2, 0.4, 0.6, 0.8, and 1. Since the experimental results showed that the initial temperature was directly proportional to the number of points, the optimal bipolarization result was not obtained. Therefore, four more sets of experiments were set with initial temperatures of 0.3, 0.1, 0.05, and 0.025 near the initial temperature of 0.2. Finally, the optimal bipolarization result was obtained for different L values. The SA algorithm flow is as follows: Figure 2 Accepting a new solution includes accepting a solution smaller than the old solution and accepting a solution larger than the old solution with probability.

[0045] In another preferred embodiment of the point selection method for temporal InSAR image dual polarization based on any of the above preferred embodiments, this preferred embodiment provides a point selection system for temporal InSAR image dual polarization, including: The monitoring unit is used to acquire dual-polarization images of the monitoring area; The central control unit includes: The first processing module is used to construct polarization basis transformation equations based on the decomposition results of dual-polarization images; The second processing module is used to obtain the parameter distribution of the same polarization image according to the polarization basis transformation equation, and to set the initial value for optimization according to the parameter distribution of the same polarization image. The third processing module is used to generate the optimal polarization combination based on the initial optimization value and the preset optimization algorithm model, and to obtain the surface deformation points by processing the optimal polarization combination using PSInSAR technology.

[0046] In a preferred embodiment of this application, the first processing module is used for: The polarization scattering matrix [S] is constructed based on the linear relationship between the polarization terms of the radar transmitted wave and the target scattered echo; ; in, It is an electromagnetic wave. It is the natural logarithm. For the antenna to transmit waves, For the target scattered wave, The distance between the radar receiving antenna and the scattering target. and It is a homopolar combination; and It is a cross-polarization combination. Indicates the electromagnetic wave coefficient; Define the Pauli basis for the polarization scattering matrix [S]: ; in, These represent different scattering mechanisms. Let these represent the power of the scattering mechanism, respectively. According to the reciprocity theorem and the monostation system, i.e. ; The scattering matrix [S] is vectorized using the pauli basis to generate the polarization vector k; Obtain the projection vector ; Based on the polarization vector k and the projection vector Set the scattering coefficient μ; ; Indicates the conjugate operation; The polarization basis transformation equation is constructed based on the scattering coefficient μ.

[0047] Specifically, the first processing module is also used for: Establish a dual-polarization combination of VV and VH, and generate vector k based on the polarization combination. VV / VH ; ; Establish a dual-polarization combination of HH and HV, and generate vector k based on the polarization combination. HH / VH ; ; Establish a dual-polarization combination of HH and VV, and generate vector k based on the polarization combination. HH / VV;

[0048] In a preferred embodiment of this application, the second processing module is further configured to: Generate amplitude deviation under single-polarization conditions; Establish the functional relationship between the amplitude deviation exponent and the Pauli basis: ; The parameter distribution of the same polarization image was calculated based on the single threshold method.

[0049] Based on the first concept of this application, by constructing a polarization basis transformation equation and obtaining the optimal polarization combination for the point selection method through an optimization model, more deformation points can be extracted in the entire monitoring area. Under the premise of ensuring the accuracy of deformation points, the deformation points are made as dense as possible. The nearest neighbor method is used to verify the accuracy of the deformation rate of single polarization (HH polarization) and OPT polarization. The density of deformation points is compared by the distribution of the number of points.

[0050] According to the second concept of this application, the initial value for optimization is set according to the distribution of the same polarization image parameters, which ensures that the optimization process quickly converges to the vicinity of the physically meaningful global optimum, avoiding getting trapped in local optima or wasting computational resources, and saving computation time.

[0051] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application.

Claims

1. A point selection method for dual polarization of temporal InSAR images, characterized in that, include: Collect dual-polarization images of the monitoring area and construct polarization basis transformation equations based on the decomposition results of the dual-polarization images; The parameter distribution of the dual-polarization image is obtained according to the polarization basis transformation equation, and the initial value for optimization is set according to the parameter distribution of the dual-polarization image. The optimal polarization combination is generated based on the initial optimization value and the preset optimization algorithm model. The surface deformation points are obtained by PSInSAR technology based on the optimal polarization combination.

2. The point selection method for time-series InSAR image dual polarization as described in claim 1, characterized in that, The construction of the polarization basis transformation equation includes: The polarization scattering matrix [S] is constructed based on the linear relationship between the polarization terms of the radar transmitted wave and the target scattered echo; ; in, It is an electromagnetic wave. It is the natural logarithm. For the antenna to transmit waves, For the target scattered wave, The distance between the radar receiving antenna and the scattering target. and It is a homopolar combination; and It is a cross-polarization combination. Indicates the electromagnetic wave coefficient; Define the Pauli basis for the polarization scattering matrix [S]: ； in, These represent different scattering mechanisms. Let these represent the power of the scattering mechanism, respectively. According to the reciprocity theorem and the monostation system, i.e. ; The scattering matrix [S] is vectorized using the pauli basis to generate the polarization vector k.

3. The point selection method for time-series InSAR image dual polarization as described in claim 2, characterized in that, When constructing the polarization basis transformation equation, the following is also included: Obtain the projection vector ; Based on the polarization vector k and the projection vector Set the scattering coefficient μ; ； Indicates the conjugate operation; The polarization basis transformation equation is constructed based on the scattering coefficient μ.

4. The point selection method for time-series InSAR image dual polarization as described in claim 3, characterized in that, The generated polarization vector k also includes: Establish a dual-polarization combination of VV and VH, and generate vector k based on the polarization combination. VV / VH ; ; Establish a dual-polarization combination of HH and HV, and generate vector k based on the polarization combination. HH / VH ; ; Establish a dual-polarization combination of HH and VV, and generate vector k based on the polarization combination. HH / VV; 。 5. The point selection method for time-series InSAR image dual polarization as described in claim 4, characterized in that, The parameter distribution of co-polarized images is obtained based on the polarization basis transform equation, including: Generate amplitude deviation under single-polarization conditions; Establish the functional relationship between the amplitude deviation exponent and the Pauli basis: ； The parameter distribution of the same polarization image was calculated based on the single threshold method.

6. A point selection system for dual polarization of temporal InSAR images, employing the point selection method for dual polarization of temporal InSAR images according to any one of claims 1-5, characterized in that, include: The monitoring unit is used to acquire dual-polarization images of the monitoring area; The central control unit includes: The first processing module is used to construct polarization basis transformation equations based on the decomposition results of dual-polarization images; The second processing module is used to obtain the parameter distribution of the same polarization image according to the polarization basis transformation equation, and to set the initial value for optimization according to the parameter distribution of the same polarization image. The third processing module is used to generate the optimal polarization combination based on the initial optimization value and the preset optimization algorithm model, and to obtain the surface deformation points by processing the optimal polarization combination using PSInSAR technology.

7. The point selection system for time-series InSAR image dual polarization as described in claim 6, characterized in that, The first processing module is used for: The polarization scattering matrix [S] is constructed based on the linear relationship between the polarization terms of the radar transmitted wave and the target scattered echo; ; in, It is an electromagnetic wave. It is the natural logarithm. For the antenna to transmit waves, For the target scattered wave, The distance between the radar receiving antenna and the scattering target. and It is a homopolar combination; and It is a cross-polarization combination. Indicates the electromagnetic wave coefficient; Define the Pauli basis for the polarization scattering matrix [S]: ； in, These represent different scattering mechanisms. Let these represent the power of the scattering mechanism, respectively. According to the reciprocity theorem and the monostation system, i.e. ; The scattering matrix [S] is vectorized using the pauli basis to generate the polarization vector k; Obtain the projection vector ; Based on the polarization vector k and the projection vector Set the scattering coefficient μ; ； Indicates the conjugate operation; Construct the polarization basis transformation equation based on the scattering coefficient μ; Establish a dual-polarization combination of VV and VH, and generate vector k based on the polarization combination. VV / VH ; ; Establish a dual-polarization combination of HH and HV, and generate vector k based on the polarization combination. HH / VH ; ; Establish a dual-polarization combination of HH and VV, and generate vector k based on the polarization combination. HH / VV; 。 8. The point selection system for time-series InSAR image dual polarization as described in claim 7, characterized in that, The second processing module is further configured to: Generate amplitude deviation under single-polarization conditions; Establish the functional relationship between the amplitude deviation exponent and the Pauli basis: ； The parameter distribution of the same polarization image was calculated based on the single threshold method.

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