Method and related equipment for monitoring surface deformation of power transmission lines based on PS-InSAR technology

Abstract

The present application provides a method and related equipment for monitoring the surface deformation of power transmission lines based on PS-InSAR technology: selecting a main image and n auxiliary images for registration and interference processing, generating a time series correlation coefficient sequence and n interference phase diagrams for each pixel in the main image; selecting permanent scatterer points based on the time series correlation coefficient sequence; calculating the time series interference phase sequence of the permanent scatterer points, and selecting reference points based on the time series interference phase sequence; connecting the reference points in the main image based on a preset distance condition to generate a reference network, in which every two connected reference points in the reference network form a reference point pair; calculating the differential interference phase matrix of the two reference points forming the reference point pair; performing phase unwrapping on the differential interference phase matrix to obtain the surface deformation amount. The method provided in the present application selects reference points with high stability based on two conditions, is suitable for monitoring the surface deformation of power transmission lines, and can obtain more accurate surface deformation amounts.

Description

Technical Field

[0001] The present application relates to the field of synthetic aperture radar interferometry technology, and in particular to a method for monitoring surface deformation of a power transmission line based on PS-InSAR technology and related equipment. Background Art

[0002] There are a large number of mountainous areas along the power lines, and there are many potential geological risks under the influence of rainfall and geological environment. As a cutting-edge technology, remote sensing satellite monitoring of transmission lines has the characteristics of large coverage, small environmental impact, and fast revisit speed. It provides a reliable data source and auxiliary decision-making information for normal inspections in uninhabited areas and special inspections for disaster emergencies, and is an important guarantee for the safe and stable operation of the power Internet of Things and power grids.

[0003] Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology is developed on the basis of Differential Interferometric Synthetic Aperture Radar (D-InSAR). Conventional D-InSAR technology has the problems of target point decoherence and difficulty in removing atmospheric delay, while PS-InSAR technology solves the above problems by tracking the PS points of permanent scatterers in the target area. These PS points are almost not affected by the image of decoherence noise. By performing time series analysis on the PS points, the influence of the atmosphere can be eliminated and more accurate deformation can be obtained.

[0004] At present, PS-InSAR technology is mostly used to monitor areas with large surface deformation changes, such as landslides and large buildings. However, for targets such as transmission lines, where the surface deformation is displayed in a small range in the image, the method of selecting PS points in related technologies is not applicable, resulting in low measurement accuracy. At present, there is still a lack of a suitable method for monitoring the surface deformation of transmission lines. Therefore, providing a PS-InSAR method that can be used to monitor the surface deformation of transmission lines is an urgent problem that technicians in this field need to solve. Summary of the invention

[0005] In view of this, the purpose of this application is to propose a method and related equipment for monitoring surface deformation of transmission lines based on PS-InSAR technology.

[0006] Based on the above objectives, the present application provides a method for monitoring surface deformation of a transmission line based on PS-InSAR technology, comprising:

[0007] Collecting SAR images of the target area at different time points by using synthetic aperture radar SAR, and selecting a main image and n auxiliary images from the SAR images based on the time points;

[0008] The n auxiliary images are respectively registered and interfered with the main image to generate a time series correlation coefficient sequence and n interference phase maps for each pixel in the main image;

[0009] For the time series correlation coefficient sequence of each pixel, in response to determining that each correlation coefficient in the time series correlation coefficient sequence is greater than a first threshold, determining the pixel as a permanent scatterer point;

[0010] For each of the permanent scatterer points, obtaining a time-series interference phase sequence of the permanent scatterer point based on the n interference phase images, and in response to determining that the time-series interference phase sequence meets a first predetermined requirement, determining the permanent scatterer point as a reference point;

[0011] Connecting the reference points in the main image based on a preset distance condition to generate a reference network, wherein every two connected reference points in the reference network constitute a reference point pair;

[0012] For each of the reference points, a first interference phase of the reference point is obtained in the nth interference phase image, an error phase in the first interference phase is removed to obtain a second interference phase of the reference point, and a difference between the second interference phases of the two reference points constituting the reference point pair is calculated to obtain a differential interference phase;

[0013] A differential interference phase matrix is ​​obtained based on the n interference phase images, and phase unwrapping is performed on the differential interference phase matrix to obtain the surface deformation amount.

[0014] Based on the same inventive concept, the present application also provides a device for monitoring the surface deformation of a transmission line based on PS-InSAR technology, comprising:

[0015] The primary and secondary image modules are configured to collect SAR images of a target area at different time points through a synthetic aperture radar SAR, and select a primary image and n secondary images from the SAR images based on the time points;

[0016] An interference processing module, configured to perform registration and interference processing on the n auxiliary images and the main image respectively, to generate a time series correlation coefficient sequence and n interference phase images for each pixel in the main image;

[0017] A permanent scatterer point module is configured to determine, for each pixel's time series correlation coefficient sequence, in response to determining that each correlation coefficient in the time series correlation coefficient sequence is greater than a first threshold, the pixel as a permanent scatterer point;

[0018] A reference point module is configured to obtain, for each permanent scatterer point, a time-series interference phase sequence of the permanent scatterer point based on the n interference phase images, and determine the permanent scatterer point as a reference point in response to determining that the time-series interference phase sequence meets a first predetermined requirement;

[0019] A reference network module is configured to connect the reference points in the main image based on a preset distance condition to generate a reference network, wherein every two connected reference points in the reference network form a reference point pair;

[0020] A differential interference phase module is configured to obtain, for each reference point, a first interference phase of the reference point in the nth interference phase image, remove the error phase in the first interference phase to obtain a second interference phase of the reference point, and calculate a difference between the second interference phases of two reference points constituting the reference point pair to obtain a differential interference phase;

[0021] The phase unwrapping module is configured to obtain a differential interference phase matrix based on the n interference phase images, and perform phase unwrapping on the differential interference phase matrix to obtain the surface deformation amount.

[0022] Based on the same inventive concept, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described above when executing the program.

[0023] Based on the same inventive concept, the present application also provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute the method as described above.

[0024] From the above, it can be seen that the method and related equipment for monitoring the surface deformation of power transmission lines based on PS-InSAR technology provided by this application align and interfere the main image and the auxiliary image to generate an interference phase map, determine the reference point according to the time series correlation coefficient and the time series interference phase sequence of each pixel in the main image, build a reference network, obtain the differential interference phase matrix between the reference point pairs based on the interference phase map and the reference network, and obtain the surface deformation variable by phase unwrapping. This application selects permanent scatterer reference points based on the two conditions of the time series correlation coefficient of the pixel and the time series interference phase sequence, so that the selected reference points have higher stability and are suitable for the observation of surface deformation of transmission lines; the differential interference phase is calculated after removing the error phase from the interference phase of the high-stability reference point, which can eliminate the influence of error factors such as atmospheric delay and noise, thereby obtaining a more accurate surface deformation variable. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 A schematic diagram of a process of monitoring surface deformation of a power transmission line based on PS-InSAR technology according to an embodiment of the present application;

[0027] Figure 2 A schematic diagram of average intensities of candidate primary and secondary images according to an embodiment of the present application;

[0028] Figure 3 A schematic diagram of an interference phase diagram of the auxiliary image 20191004 and the main image according to an embodiment of the present application;

[0029] Figure 4 A schematic diagram of an interference phase diagram of the auxiliary image 20191203 and the main image according to an embodiment of the present application;

[0030] Figure 5 A reference point diagram of an embodiment of the present application;

[0031] Figure 6 A schematic diagram of a reference network along a power transmission line according to an embodiment of the present application;

[0032] Figure 7 A deformation rate statistical histogram of the reference point change of the embodiment of the present application;

[0033] Figure 8 A deformation rate distribution diagram of a reference point change according to an embodiment of the present application;

[0034] Fig. 9 This is a schematic diagram of the structure of a device for monitoring surface deformation of a power transmission line based on PS-InSAR technology according to an embodiment of the present application;

[0035] Fig.10 A schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0037] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0038] As described in the background technology, traditional D-InSAR methods mainly include two-track method and three-track method. The basic idea of ​​the two-track method is to generate interference fringe patterns using two images before and after the surface changes in the test area, and then use the pre-acquired digital elevation model (DEM) data to simulate the fringe pattern, remove the terrain information from the interference pattern, and obtain the surface deformation information. The advantage of this method is that there is no need to untangle the phase of the interference pattern, avoiding the difficulty of untangle. Its disadvantage is that the two-track method cannot be used for areas without DEM data, and when introducing DEM data, new errors may be introduced, such as the elevation error of the DEM itself, the registration error between the DEM simulated interference phase and the real SAR fringe pattern, etc. The basic principle of the three-track method is to generate two interference fringe patterns using three-view images, one reflecting the terrain information and the other reflecting the surface deformation information. The main advantage of the three-track method is that it does not require auxiliary DEM data, which is particularly important for some changes without terrain data, and the registration between data is easier to achieve; the disadvantage is that the final result is heavily dependent on the quality of phase untangle.

[0039] Due to the influence of regional vegetation coverage and the large amount of settlement in a short period of time, the target point may be decoherent over a long period of time. Traditional D-InSAR technology is susceptible to decoherence and atmospheric inhomogeneity delay effects, and when the terrain phase is removed by differential processing, the accuracy requirements of the auxiliary DEM are also very high. When conducting long-term slow surface deformation monitoring, it is difficult to obtain high-precision deformation results, and it is difficult to be widely used in actual engineering.

[0040] Through long-term and extensive research, it is found that there are still high-coherence points with stable phase and amplitude changes on long-term SAR images. By processing the phase information on these high-coherence points, the influence of temporal and spatial incoherence and atmospheric inhomogeneity delay can be overcome to a large extent, and the deformation phase, DEM error phase and atmospheric delay phase can be effectively separated, thereby achieving large-scale and high-precision surface deformation inversion. These high-coherence points are PS points. By performing time series analysis on PS points, the influence of the atmosphere can be eliminated and more accurate deformation can be obtained. At present, the deformation accuracy obtained based on PS-InSAR technology can reach the millimeter level.

[0041] The methods for selecting PS points in related technologies include the coherence coefficient method, the amplitude deviation index method, etc. These methods are usually suitable for monitoring areas with large surface deformation changes such as landslides and large buildings. However, for targets such as power transmission lines whose surface deformation appears in a small range in the image, the methods for selecting PS points in related technologies are not applicable, resulting in low measurement accuracy.

[0042] The present application proposes a method and related equipment for monitoring the surface deformation of power transmission lines based on PS-InSAR technology, which performs registration and interference processing on the main and auxiliary images to generate an interference phase map, and obtains a high-stability reference point suitable for surface deformation observation of the transmission line based on the time-series correlation coefficient and the time-series interference phase sequence of each pixel in the main image. The error phase is removed from the interference phase of the reference point to eliminate the influence of error factors such as atmospheric delay and noise, and then the differential interference phase matrix of the reference point is calculated to perform phase unwrapping to obtain a more accurate surface deformation variable.

[0043] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0044] This application provides a method for monitoring the surface deformation of power transmission lines based on PS-InSAR technology. Figure 1 , including the following steps:

[0045] Step S101, collecting SAR images of a target area at different time points by using a synthetic aperture radar SAR, and selecting a main image and n auxiliary images from the SAR images based on the time points;

[0046] Specifically, in this embodiment, synthetic aperture radar (SAR) is used to collect SAR images of the target area at different time points, and a main image and n auxiliary images are selected based on the acquisition time of multiple SAR images. The main and auxiliary images are selected based on the time characteristics, which lays the foundation for the subsequent calculation of the time series characteristics of the pixels.

[0047] Step S102, registering and interfering the n auxiliary images with the main image respectively, to generate a time series correlation coefficient sequence and n interference phase maps for each pixel in the main image;

[0048] Specifically, in this embodiment, n auxiliary images are respectively registered and interfered with the main image, the registration process generates a time series correlation coefficient sequence of each pixel in the main image, and the interference process generates n interference phase images with time series characteristics.

[0049] Step S103, for the time series correlation coefficient sequence of each pixel, in response to determining that each correlation coefficient in the time series correlation coefficient sequence is greater than a first threshold, determining the pixel as a permanent scatterer point;

[0050] Specifically, in this embodiment, each pixel of the main image corresponds to a time series correlation coefficient sequence. If each correlation coefficient value in the time series correlation coefficient sequence of a certain pixel is greater than the first threshold, the pixel is determined as a permanent scatterer point. This step is the first screening of pixel points based on the correlation coefficient, and pixels with high correlation coefficients, that is, pixels that are relatively stable in the time series, can be screened out.

[0051] Step S104, for each permanent scatterer point, obtaining a time-series interference phase sequence of the permanent scatterer point based on the n interference phase images, and in response to determining that the time-series interference phase sequence meets a first predetermined requirement, determining the permanent scatterer point as a reference point;

[0052] Specifically, in this embodiment, the time-series interference phase sequence of each permanent scatterer point is obtained in n interference phase images with time-series characteristics. If the time-series interference phase sequence of a permanent scatterer point meets the first predetermined requirement, the permanent scatterer point is determined as the reference point. This step is a second screening of pixel points based on the time-series interference phase sequence. On the basis of the permanent scatterer points screened in the first step, points with stable interference phase changes are selected, which further improves the stability of the reference point and is suitable for surface deformation observation of power transmission lines.

[0053] Step S105, connecting the reference points in the main image based on a preset distance condition to generate a reference network, wherein every two connected reference points in the reference network constitute a reference point pair;

[0054] Specifically, in this embodiment, the reference points in the main image are connected based on a preset distance condition to obtain a reference network, and every two connected reference points in the reference network constitute a reference point pair.

[0055] Step S106, for each reference point, obtaining a first interference phase of the reference point in the nth interference phase image, removing the error phase in the first interference phase to obtain a second interference phase of the reference point, and calculating a difference between the second interference phases of two reference points constituting the reference point pair to obtain a differential interference phase;

[0056] Specifically, in this embodiment, in the nth interference phase diagram, the first interference phase of each reference point is obtained, and the error phase in the first interference phase is removed to obtain the second phase of each reference point. For two reference points in a pair of reference point pairs, the difference between the second phases of the two reference points is calculated to obtain the differential interference phase of the reference point pair, thereby obtaining the differential interference phase between all reference point pairs on the nth interference phase diagram.

[0057] Step S107, obtaining a differential interference phase matrix based on the n interference phase images, performing phase unwrapping on the differential interference phase matrix, and obtaining a surface deformation amount.

[0058] Specifically, in this embodiment, the differential interference phase matrix of all reference point pairs is calculated based on n interference phase images, the matrix is ​​phase unwrapped, and the unwrapping result is converted into the surface deformation variable.

[0059] Combine the following Figure 2-Figure 8 An embodiment of the present invention is described in detail.

[0060] In some embodiments, the selecting a main image and n auxiliary images from the SAR images based on the time point includes: sorting the SAR images based on the time point to obtain a SAR image sequence; selecting n+1 adjacent SAR images from the SAR image sequence according to preset conditions as candidate main and auxiliary images; for each of the candidate main and auxiliary images, calculating the average intensity of the candidate main and auxiliary images; selecting the candidate main and auxiliary image with the largest average intensity as the main image, and the remaining n candidate main and auxiliary images as the auxiliary images.

[0061] Specifically, in this embodiment, the study area is the Xinyi Street area of ​​Zhuhai City, where there are a large number of mountainous areas. Under the influence of rainfall and geological environment, there are many potential geological risks along the power lines. SAR images of the Xinyi Street area of ​​Zhuhai City are collected using medium-resolution SAR, and the image information is shown in Table 1.

[0062] As shown in Table 1, a total of 25 SAR images were collected from December 20, 2018 to April 25, 2020 in the Xinyi Street area of ​​Zhuhai City. The 25 images were sorted according to the order of image acquisition time to obtain a SAR image sequence, and n+1 adjacent images located at the center position were selected from the image sequence as candidate main and auxiliary images. In this embodiment, n is set to 6, so 7 images are selected as candidate main and auxiliary images. The 7 candidate main and auxiliary images are focused and converted into SLC format images. The intensity of each pixel in each candidate main and auxiliary image is calculated. The calculation formula of the pixel intensity is I=A 2 , where I is the pixel intensity and A is the amplitude of the pixel. The average intensity of each candidate primary and secondary image is calculated based on the sum of the intensities of all pixels and the number of pixels. The larger the average intensity value, the more effective pixels there are in the image. The average intensity of the 7 candidate primary and secondary images in this embodiment is as follows: Figure 2 As shown, the image collected on 20191109, i.e. November 9, 2019, has the largest average intensity, so 20191109 is used as the main image, and the remaining 6 images are used as auxiliary images.

[0063] Table 1 SAR image information of the experimental area

[0064]

[0065] In some embodiments, the n auxiliary images are respectively registered and interfered with the main image to generate a time series correlation coefficient sequence for each pixel in the main image, including: establishing a two-dimensional coordinate system in the main image to obtain the coordinate value of each pixel in the main image; registering the nth auxiliary image with the main image, and for each pixel in the main image, obtaining the coordinate change value of the pixel on the auxiliary image; calculating the correlation coefficient of the pixel between the main image and the nth auxiliary image based on the correlation coefficient method according to the coordinate value and the coordinate change value; and registering the n auxiliary images respectively with the main image to obtain a time series correlation coefficient sequence for each pixel between the main image and the n auxiliary images.

[0066] Specifically, in this embodiment, a two-dimensional coordinate system is established in the main image to obtain the coordinate value of each pixel in the main image. Taking the X pixel as an example, the coordinate value of the X pixel in the main image is (p, q). The six auxiliary images are respectively registered with the main image. Taking the first auxiliary image 20190817 as an example, the coordinate change value (u, v) of the X pixel on the first auxiliary image is obtained. The coordinate set of all pixels in the main image is recorded as S1, and the coordinate change value on the first auxiliary image is recorded as S2. The maximum correlation coefficient method is used to calculate the complex correlation coefficient r between all pixels in the main image and the first auxiliary image. The calculation formula of r is:

[0067]

[0068] Here, * indicates conjugation.

[0069] The six auxiliary images are registered with the main image to generate the temporal correlation coefficient sequence of each pixel in the main image. Taking pixel X as an example, the temporal correlation coefficient sequence of pixel X is r1, r2, r3, r4, r5, r6.

[0070] In some embodiments, for the time series correlation coefficient sequence of each pixel, in response to determining that each correlation coefficient in the time series correlation coefficient sequence is greater than a first threshold, the pixel is determined to be a permanent scatterer point.

[0071] Specifically, in this embodiment, taking pixel X as an example, if the temporal correlation coefficient sequence r1, r2, r3, r4, r5 and r6 of pixel X are all greater than 0.9, the pixel is determined as a permanent scatterer point, thereby obtaining a permanent scatterer point set X (X1, X2...X x ).

[0072] In some embodiments, the time-series interference phase sequence of the permanent scatterer point is obtained based on the n interference phase images, and in response to determining that the time-series interference phase sequence meets a first predetermined requirement, the permanent scatterer point is determined as a reference point, including: for each permanent scatterer point, n interference phases of the permanent scatterer point are obtained based on the n interference phase images, and the time-series interference phase sequence of the permanent scatterer point is generated; the difference between two adjacent interference phases is calculated based on the time-series interference phase sequence to obtain an interference phase difference sequence of the permanent scatterer point, and a mean and a standard deviation are calculated based on the interference phase difference sequence; in response to determining that the interference phase difference sequence meets the first predetermined requirement, the permanent scatterer point is determined as the reference point, and the first predetermined requirement includes the mean and the standard deviation requirements.

[0073] Specifically, in this embodiment, the six auxiliary images are interfered with the main image to generate six interference phase images, such as Figure 3 and Figure 4 As shown, they are the interference phase images of the auxiliary images 20191004, 20191203 and the main image. It can be seen that the mountainous area is greatly affected by noise. The interference fringes mostly appear in the building areas and near the transmission towers, and obvious interference fringes also appear on some roads.

[0074] In this embodiment, for a permanent scatterer point set X(X1, X2...X x), the interference phase of each point is obtained in the 6 interference phase diagrams to form the time-series interference phase sequence of each point. Taking X1 as an example, the time-series interference phase sequence of X1 is obtained as follows: Based on the time-series interference phase sequence, the difference between two adjacent interference phases is calculated to obtain the interference phase difference sequence of the permanent scatterer point X1. The mean μ and the standard deviation δ are calculated based on the interference phase difference sequence. If the standard deviation δ of the interference phase difference sequence is greater than or equal to a preset threshold, or there is a value greater than μ±3δ in the interference phase difference sequence, then this point is removed from the set X, and finally a reference point with high stability is obtained to form a reference point set Y (Y1, Y2...Y y ). Figure 5 The reference points obtained in this embodiment are marked, and the results show that key locations such as buildings, roads, and transmission line towers are effectively selected and are distributed relatively reasonably on the transmission monitoring line.

[0075] In some embodiments, the reference points are connected in the main image based on a preset distance condition to generate a reference network, and every two connected reference points in the reference network form a reference point pair.

[0076] Specifically, in this embodiment, when establishing the reference network, firstly, a certain number of windows are divided in the entire area of ​​the main image, such as Figure 6 The figure shows a window of the main image. The size and number of windows are determined by the size of the area and the distribution of reference points. When selecting the number of windows, be careful not to select too small or too large distances between reference points to lose the control effect. Considering the strong correlation of atmospheric delay in space, the distance between adjacent reference points needs to be controlled within 1 km. Data processing experience shows that it is best to control the adjacent distance to be concentrated between 700 and 1000 meters to ensure that the atmospheric influence isotropic errors can be effectively controlled during spatial differentiation. After selecting a reasonable window size and number, based on this determination principle, there will be no reference points in some windows. The main reason is that the stability of the reference points in this area is not very good. According to the set distance conditions, the reference points are connected to establish a reference network. Every two connected reference points form a reference point pair, and their connection line forms an observation edge, called a PS baseline. Figure 6 The reference grid along the transmission line in this embodiment is shown. The distribution of these reference points can effectively serve as a reference for deformation monitoring of transmission line towers. For a few cells where no reference points exist, some irregular grids are generated for the calculation of phase integrals in unwrapping.

[0077] In some embodiments, for each of the reference points, a first interference phase of the reference point is obtained in the nth interference phase diagram, the error phase in the first interference phase is removed to obtain a second interference phase of the reference point, and the difference between the second interference phases of the two reference points constituting the reference point pair is calculated to obtain a differential interference phase; the error phase includes: a reference phase, an atmospheric delay phase, a terrain phase, a flat ground phase, and a noise phase.

[0078] Specifically, in this embodiment, for the reference point set Y (Y1, Y2...Y y ), the first interference phase of the reference point is obtained in each interference phase diagram. Taking reference point Y1 as an example, the first interference phase Φ of Y1 is obtained in the first interference phase diagram intf :

[0079]

[0080] Wherein, δR+Δd is the variation, and λ is the wavelength. The first interference phase includes the surface deformation phase Φ disp , reference phase Φ ref , atmospheric delay phase Φ atm , terrain phase Φ topo , flat ground phase Φ flat and noise phase Φ noise In order to obtain the surface deformation phase value, it is necessary to remove the remaining error phases. Among them: based on the phase of point Y1 in the main image to remove the reference phase Φ ref ;

[0081] Atmospheric model based on reference point time series inversion to remove atmospheric delay phase Φ atm ;

[0082] Removal of terrain phase Φ based on DEM topo :Using the SAR satellite orbit parameters, the simulated SAR image in the main image coordinate system is first generated externally, and then it is accurately registered with the main image to obtain the precise parameters of the coordinate system value conversion between the two. Based on this, the elevation information is converted into phase information to obtain the simulated terrain phase of the elevation, and then the terrain phase Φ is removed. topo ;

[0083] The flat-earth phase Φ that shows periodic changes is removed based on the baseline parameters and ellipsoid parameters of the reference point. flat ;

[0084] Removing the noise phase Φ based on a suitable filtering algorithm noise ;

[0085] Thus, the second interference phase of the reference point Y1 in the first interference phase diagram is obtained.

[0086] In this embodiment, assuming that two reference points constituting a pair of reference points are i and j respectively, an interference model of the second interference phase of i and j in the nth interference phase diagram can be established:

[0087]

[0088]

[0089] Among them: k is the phase integer ambiguity; β is the phase elevation conversion coefficient; ΔH is the elevation correction number; v is the settlement rate of the surface deformation at the point; λ is the wavelength of the microwaves emitted by the radar satellite; T is the time interval between the main image and the nth auxiliary image; ε is the random error, which is omitted in the unwrapping model. Then the second interferometric phase difference of point i relative to point j can be expressed as:

[0090]

[0091] in: It represents the differential interference phase of point i relative to point j in the nth interference phase diagram;

[0092] It represents the phase integer ambiguity difference of point i relative to point j in the nth interferometric phase image;

[0093] It represents the sedimentation rate difference between point i and point j in the nth interference phase diagram;

[0094] It represents the difference in elevation correction between point i and point j in the nth interferometric phase image.

[0095] In some embodiments, the phase unwrapping of the differential interference phase matrix includes: performing phase unwrapping of the differential interference phase matrix using a least squares method.

[0096] Specifically, in this embodiment, the differential interference phase matrix of point i and point j is obtained based on n interference phase images:

[0097] make

[0098] The matrix form can be further simplified as: y1 = A1·a + B1·b

[0099] In the formula, the integer phase ambiguity k, the elevation correction number ΔH and the sedimentation rate v are all unknown quantities. There are n equations and n+2 unknowns in total. Obviously, the equation is rank-deficient. Therefore, a pseudo-observation value y2=A2·a+B2·b is added to form a new model together with the above formula:

[0100] y=A·a+B·b

[0101] in: y2 is a 2*1 pseudo observation vector; A2 is a 2*n zero matrix; B2 is a 2*2 identity matrix.

[0102] According to the least squares principle, we can get:

[0103] Where: C = (AB); Q y is the variance-covariance matrix of the observed values ​​and pseudo-observations. is the floating point solution of the phase integer ambiguity. Taking this floating point solution as known data, the proposed least squares based ambiguity decorrelation method is used to search for the fixed solution of the phase integer ambiguity

[0104] Get a fixed solution After that, the unwrapped phase It can be expressed as:

[0105] At this point, the unwrapped phase can be expressed as:

[0106] Using the least squares principle again, we can get:

[0107] in: Represents the variance-covariance matrix of the second interferometric phase.

[0108] In summary, phase unwrapping is completed.

[0109] Finally, the deformation monitoring results can be obtained through phase transformation and geocoding in the remote sensing software. Figure 7 and Figure 8 As shown in the figure, the deformation rate statistical histogram and deformation rate distribution diagram of the image relative to the main image reference point before and after the main image are used as the standard, and the change rate is calculated in millimeters per year (mm / y). Figure 7 From the statistical histogram, the final statistical deformation rate distribution center of the reference point is slightly lower than 0, indicating that the area has slightly sunk, the overall deformation remains stable, and some deformation occurs in the local area. The average deformation in the area is -2.8mm / y, the local maximum sinking deformation rate is -28.26mm / y, and the local maximum lifting deformation rate is 22.65mm / y.

[0110] When this method is used for unwrapping, there are many reference points, which can effectively reduce the propagation of errors and errors caused by elevation differences. The results show that when the present invention is used for deformation monitoring in mountainous areas where power transmission lines are located, there are fewer unwrapping noise points and a larger effective monitoring area, showing great advantages in deformation monitoring along power transmission lines.

[0111] It should be noted that the method of the embodiment of the present application can be performed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present application, and the multiple devices will interact with each other to complete the described method.

[0112] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0113] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a device for monitoring the surface deformation of a transmission line based on PS-InSAR technology, referring to Fig. 9 The device for monitoring the surface deformation of a power transmission line based on PS-InSAR technology comprises:

[0114] The primary and secondary image module 901 is configured to collect SAR images of a target area at different time points through a synthetic aperture radar SAR, and select a primary image and n secondary images from the SAR images based on the time points;

[0115] The interference processing module 902 is configured to perform registration and interference processing on the n auxiliary images and the main image respectively, and generate a time series correlation coefficient sequence and n interference phase images for each pixel in the main image;

[0116] The permanent scatterer point module 903 is configured to, for the time series correlation coefficient sequence of each pixel, determine the pixel as a permanent scatterer point in response to determining that each correlation coefficient in the time series correlation coefficient sequence is greater than a first threshold;

[0117] The reference point module 904 is configured to obtain, for each permanent scatterer point, a time-series interference phase sequence of the permanent scatterer point based on the n interference phase images, and determine the permanent scatterer point as a reference point in response to determining that the time-series interference phase sequence meets a first predetermined requirement;

[0118] A reference network module 905 is configured to connect the reference points in the main image based on a preset distance condition to generate a reference network, wherein every two connected reference points in the reference network constitute a reference point pair;

[0119] The differential interference phase module 906 is configured to obtain, for each reference point, a first interference phase of the reference point in the nth interference phase image, remove the error phase in the first interference phase to obtain a second interference phase of the reference point, and calculate the difference between the second interference phases of the two reference points constituting the reference point pair to obtain a differential interference phase;

[0120] The phase unwrapping module 907 is configured to obtain a differential interference phase matrix based on the n interference phase images, and perform phase unwrapping on the differential interference phase matrix to obtain the surface deformation amount.

[0121] For the convenience of description, the above device is described in terms of functions divided into various modules. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0122] The device of the above embodiment is used to implement the corresponding method of monitoring the surface deformation of the power transmission line based on the PS-InSAR technology in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0123] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for monitoring the surface deformation of a transmission line based on the PS-InSAR technology as described in any of the above embodiments is implemented.

[0124] Fig.10 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0125] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0126] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0127] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0128] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0129] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0130] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0131] The electronic device of the above embodiment is used to implement the corresponding method of monitoring the surface deformation of the power transmission line based on the PS-InSAR technology in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0132] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method for monitoring the surface deformation of the transmission line based on the PS-InSAR technology as described in any of the above embodiments.

[0133] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0134] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the method for monitoring surface deformation of transmission lines based on PS-InSAR technology as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0135] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0136] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0137] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0138] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.

Claims

1. A method for monitoring surface deformation of power transmission lines based on PS-InSAR technology, characterized in that: include: Collecting SAR images of a target area at different time points through a synthetic aperture radar SAR, sorting the SAR images based on the time points to obtain a SAR image sequence; selecting n+1 adjacent SAR images from the SAR image sequence according to preset conditions as candidate main and auxiliary images; and calculating the average intensity of each candidate main and auxiliary image; Select the candidate main and auxiliary images with the largest average intensity as the main image, and the remaining n candidate main and auxiliary images as the auxiliary images; The n auxiliary images are respectively registered and interfered with the main image to generate a time series correlation coefficient sequence and n interference phase maps for each pixel in the main image; For the time series correlation coefficient sequence of each pixel, in response to determining that each correlation coefficient in the time series correlation coefficient sequence is greater than a first threshold, determining the pixel as a permanent scatterer point; For each of the permanent scatterer points, obtaining a time-series interference phase sequence of the permanent scatterer point based on the n interference phase images, and in response to determining that the time-series interference phase sequence meets a first predetermined requirement, determining the permanent scatterer point as a reference point; Connecting the reference points in the main image based on a preset distance condition to generate a reference network, wherein every two connected reference points in the reference network constitute a reference point pair; For each of the reference points, a first interference phase of the reference point is obtained in the nth interference phase image, an error phase in the first interference phase is removed to obtain a second interference phase of the reference point, and a difference between the second interference phases of the two reference points constituting the reference point pair is calculated to obtain a differential interference phase; A differential interference phase matrix is ​​obtained based on the n interference phase images, and phase unwrapping is performed on the differential interference phase matrix to obtain the surface deformation amount.

2. The method according to claim 1, characterized in that The step of registering and interfering the n auxiliary images with the main image to generate a time series correlation coefficient sequence for each pixel in the main image includes: Establishing a two-dimensional coordinate system in the main image to obtain the coordinate value of each pixel in the main image; Registering the nth auxiliary image with the main image, and obtaining, for each pixel in the main image, a coordinate change value of the pixel on the auxiliary image; Calculating the correlation coefficient between the pixel in the main image and the n-th auxiliary image based on the correlation coefficient method according to the coordinate value and the coordinate change value; The n auxiliary images are respectively registered with the main image to obtain a time-series correlation coefficient sequence between each pixel in the main image and the n auxiliary images.

3. The method according to claim 1, characterized in that The step of obtaining the time-series interference phase sequence of the permanent scatterer point based on the n interference phase images, and determining the permanent scatterer point as a reference point in response to determining that the time-series interference phase sequence meets a first predetermined requirement, comprises: For each of the permanent scatterer points, obtaining n interference phases of the permanent scatterer point based on the n interference phase images, and generating the time-series interference phase sequence of the permanent scatterer point; Calculating the difference between two adjacent interference phases based on the time-series interference phase sequence to obtain an interference phase difference sequence of the permanent scatterer point, and calculating the mean and standard deviation based on the interference phase difference sequence; In response to determining that the interference phase difference sequence meets the first predetermined requirement, the permanent scatterer point is determined as the reference point, and the first predetermined requirement includes the mean value and the standard deviation requirement.

4. The method according to claim 1, characterized in that: The error phase includes: a reference phase, an atmospheric delay phase, a terrain phase, a flat ground phase and a noise phase.

5. The method according to claim 1, characterized in that The phase unwrapping of the differential interference phase matrix includes: performing phase unwrapping of the differential interference phase matrix using a least squares method.

6. A device for monitoring surface deformation of power transmission lines based on PS-InSAR technology, characterized in that: include: The primary and secondary image module is configured to collect SAR images of a target area at different time points through a synthetic aperture radar SAR, sort the SAR images based on the time points to obtain a SAR image sequence; select n+1 adjacent SAR images from the SAR image sequence according to preset conditions as candidate primary and secondary images; and calculate the average intensity of each candidate primary and secondary image; Select the candidate main and auxiliary images with the largest average intensity as the main image, and the remaining n candidate main and auxiliary images as the auxiliary images; An interference processing module, configured to perform registration and interference processing on the n auxiliary images and the main image respectively, to generate a time series correlation coefficient sequence and n interference phase images for each pixel in the main image; A permanent scatterer point module is configured to determine, for each pixel's time series correlation coefficient sequence, in response to determining that each correlation coefficient in the time series correlation coefficient sequence is greater than a first threshold, the pixel as a permanent scatterer point; A reference point module is configured to obtain, for each permanent scatterer point, a time-series interference phase sequence of the permanent scatterer point based on the n interference phase images, and determine the permanent scatterer point as a reference point in response to determining that the time-series interference phase sequence meets a first predetermined requirement; A reference network module is configured to connect the reference points in the main image based on a preset distance condition to generate a reference network, wherein every two connected reference points in the reference network form a reference point pair; A differential interference phase module is configured to obtain, for each reference point, a first interference phase of the reference point in the nth interference phase image, remove the error phase in the first interference phase to obtain a second interference phase of the reference point, and calculate a difference between the second interference phases of two reference points constituting the reference point pair to obtain a differential interference phase; The phase unwrapping module is configured to obtain a differential interference phase matrix based on the n interference phase images, and perform phase unwrapping on the differential interference phase matrix to obtain the surface deformation amount.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 5 is implemented.

8. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 5.

Images