Electric tower deformation monitoring method and device based on GB-SAR and corner reflector

Abstract

The invention relates to the technical field of deformation monitoring, and discloses an electric tower deformation monitoring method and device based on a GB-SAR and a corner reflector, and the method comprises the steps: collecting a plurality of imaging radar images corresponding to a target electric tower through ground-based synthetic aperture radar equipment; taking pixel points simultaneously existing in all imaging radar images as candidate pixel points; a coherent coefficient and an amplitude discrete index of each candidate pixel point are calculated, and a persistent scatterer is selected from the candidate pixel points, so that a meteorological correction triangulation network is constructed; performing meteorological disturbance removal processing on each imaging radar image according to the meteorological correction triangulation network to form a processed imaging radar image; phase difference data of a target electric tower is obtained by adopting a differential interference measurement technology, displacement analysis is carried out on the phase difference data, the earth surface deformation phase difference of the target electric tower can be obtained, and therefore the deformation degree of the target electric tower is determined. According to the invention, the quality of the monitoring image is improved, and the monitoring precision and accuracy of electric tower deformation monitoring are also improved.

Description

Technical Field

[0001] The present invention relates to the technical field of deformation monitoring, and particularly to a method and device for monitoring the deformation of an electric tower based on GB-SAR and a corner reflector. Background Art

[0002] In recent years, the construction of power transmission lines has been accelerating continuously. Especially, the construction scale of ultra-high voltage power transmission lines has been increasing continuously. The geological environment along the high-voltage power transmission lines is complex and diverse, and the hidden dangers of disaster weather and geological disasters affect the safe operation of the power transmission lines. At present, the monitoring of the power grid operation status mainly includes various monitoring methods such as on-line monitoring of sensors, manual inspection, unmanned aerial vehicle inspection, helicopter inspection, robot inspection, and infrared imaging temperature measurement instrument. These monitoring technologies still have deficiencies in the case of slow and tiny deformations and tower inclinations caused by environmental impacts on transmission towers, and it is difficult to meet the requirements of high-precision, non-contact, and remote telemetry. Therefore, the status data of the transmission tower affects the accuracy of the power grid operation status.

[0003] Currently, the ground-based SAR technology is often used to monitor the deformation of transmission towers, and the surface deformation information is obtained by calculating the phase difference between two SAR images. This technology is widely used in various deformation monitoring, such as urban ground subsidence, infrastructure deformation, landslide disasters and other fields. However, this monitoring technology is greatly affected by environmental factors such as weather, resulting in low-precision images collected, thus affecting the monitoring accuracy and accuracy of deformation monitoring. Summary of the Invention

[0004] The present invention provides a method and device for monitoring the deformation of an electric tower based on GB-SAR and a corner reflector, which improves the monitoring accuracy and accuracy of the deformation monitoring of the electric tower.

[0005] In order to solve the above technical problems, the present invention provides a method for monitoring the deformation of an electric tower based on GB-SAR and a corner reflector, including:

[0006] Using a GB-SAR device to respectively collect a plurality of imaging radar images of a target monitoring area where a target electric tower is located; wherein, a plurality of corner reflectors are arranged on the target electric tower;

[0007] Comparing and analyzing each of the imaging radar images, and taking the pixel points that exist in all of the imaging radar images as candidate pixel points;

[0008] Selecting PSC points from each of the candidate pixel points by calculating the coherence coefficient and amplitude dispersion index of each of the candidate pixel points;

[0009] Based on each of the PSC points, constructing a meteorological correction triangular network covering the target monitoring area;

[0010] According to the meteorological correction triangular network, perform meteorological disturbance removal processing on each of the imaging radar images to form a number of processed imaging radar images;

[0011] Adopt differential interferometry measurement technology to obtain the phase difference data of the target power tower among a number of the processed imaging radar images;

[0012] Through displacement analysis of the phase difference data of the target power tower, calculate the surface deformation phase difference of the target power tower, and determine the deformation degree of the target power tower according to the surface deformation phase difference.

[0013] As a preferred solution, the selecting PSC points among each of the candidate pixel points by calculating the coherence coefficient and amplitude dispersion index of each of the candidate pixel points includes:

[0014] Select PS points among each of the candidate pixel points by calculating the coherence coefficient of each of the candidate pixel points;

[0015] Select PSC points among each of the PS points by calculating the amplitude dispersion index of each of the PS points.

[0016] As a preferred solution, the selecting PS points among each of the candidate pixel points by calculating the coherence coefficient of each of the candidate pixel points includes:

[0017] Calculate the coherence coefficient of each of the candidate pixel points through the following formula:

[0018]

[0019] In the formula, γ n is the coherence coefficient of the nth candidate pixel point; E{·} is the expectation operator; z1 and z2 are the complex values of two adjacent imaging radar images respectively; is the complex conjugate of z2; |·| is the absolute value operator;

[0020] Calculate the mean value of the coherence coefficients according to the coherence coefficients of each of the candidate pixel points;

[0021] Determine the candidate pixel points with coherence coefficients greater than the mean value of the coherence coefficients as PS points.

[0022] As a preferred solution, the selecting PSC points among each of the PS points by calculating the amplitude dispersion index of each of the PS points includes:

[0023] Calculate the amplitude dispersion index of each of the PS points through the following formula, specifically:

[0024]

[0025] In the formula, D a,psis the amplitude discrete index of the PS point; σ a,ps is the amplitude standard deviation of the PS point; m a,ps is the average amplitude of the PS point;

[0026] Obtain the preset amplitude discrete index threshold;

[0027] Determine the PS points with an amplitude discrete index less than the preset amplitude discrete index threshold as PSC points.

[0028] As a preferred solution, the meteorological disturbance removal process is respectively performed on each of the imaging radar images according to the meteorological correction triangular network to form a plurality of processed imaging radar images, including:

[0029] For each pixel point in the imaging radar image, determine the triangle in the meteorological correction triangular network where the pixel point is located;

[0030] Respectively calculate the distance data between the pixel point and a plurality of PSC points in the triangle;

[0031] Determine the weight of the pixel point according to the distance data;

[0032] Perform weighted correction on the pixel point according to the weight to form a processed imaging radar image.

[0033] As a preferred solution, the differential interferometry measurement technique is used to obtain the phase difference data of the target electric tower in a plurality of the processed imaging radar images, including:

[0034] Based on the differential interferometry measurement technique, perform pixel co-multiplication processing on two adjacent processed imaging radar images to obtain a plurality of interferometric phase images;

[0035] Respectively determine the target pixel points corresponding to the target electric tower in each of the interferometric phase images;

[0036] Respectively obtain the phase differences of the target pixel points in each of the interferometric phase images;

[0037] Determine the phase differences of all the target pixel points as the phase difference data of the target electric tower;

[0038] Among them, the phase differences of the target pixel points are respectively obtained in each of the interferometric phase images through the following formula, including:

[0039]

[0040] In the formula, Δφ(P) is the phase difference of the target pixel point P; I1(P) and I2(P) are the complex values of two interferometric phase images respectively; is the complex conjugate of I1(P); ∠(·) is the phase angle operator; φ1(P) is the phase of the target pixel point P in I1(P); φ2(P) is the phase of the target pixel point P in I2(P).

[0041] As a preferred solution, by performing displacement analysis on the phase difference data of the target electric tower, calculating the surface deformation phase difference of the target electric tower, and determining the deformation degree of the target electric tower according to the surface deformation phase difference, it includes:

[0042] By performing displacement analysis on the phase difference data of the target electric tower, determining the phase change law of the target electric tower;

[0043] Calculating the integer ambiguity according to the phase change law of the target electric tower;

[0044] Calculating the surface deformation phase difference of the target electric tower according to the phase difference data of the target electric tower and the integer ambiguity;

[0045] Determining the deformation degree of the target electric tower according to the surface deformation phase difference of the target electric tower.

[0046] As a preferred solution, the calculating the surface deformation phase difference of the target electric tower according to the phase difference data of the target electric tower and the integer ambiguity includes:

[0047]

[0048] In the formula, is the surface deformation phase difference of the target electric tower; Δφ(P) is the phase difference of the target pixel point P; n is the integer ambiguity.

[0049] As a preferred solution, after using the GB-SAR device to collect a plurality of imaging radar images of the target monitoring area where the target electric tower is located, it further includes:

[0050] For each imaging radar image, determining the phase vectors of all pixel points in the imaging radar image;

[0051] Performing a summation process on the phase vectors of all the pixel points to obtain the main vector;

[0052] Respectively calculating a plurality of phase angle differences between all the pixel points and the main vector;

[0053] Determining the median of the phase differences among the plurality of phase angle differences;

[0054] Based on the median of the phase differences, determining the phase difference weights corresponding to the respective phase angle differences;

[0055] Perform weighted summation processing based on a plurality of the phase angle differences and the phase difference weight values corresponding to the respective phase angle differences to obtain a summation result;

[0056] Based on the summation result and the main vector phase angle corresponding to the main vector, obtain an imaging radar image with noise removed.

[0057] Correspondingly, the present invention provides an electric tower deformation monitoring device based on GB-SAR and a corner reflector, including: a data acquisition module, a first screening module, a second screening module, a construction module, an image processing module, an image interference module, and a deformation analysis module;

[0058] The data acquisition module is used to respectively acquire a plurality of imaging radar images of a target monitoring area where a target electric tower is located by using a GB-SAR device; wherein, a plurality of corner reflectors are arranged on the target electric tower;

[0059] The first screening module is used to perform comparative analysis on each of the imaging radar images, and use the pixel points that exist in all the imaging radar images simultaneously as candidate pixel points;

[0060] The second screening module is used to select PSC points from each of the candidate pixel points by calculating the coherence coefficient and the amplitude dispersion index of each of the candidate pixel points;

[0061] The construction module is used to construct a meteorological correction triangular network covering the target monitoring area based on each of the PSC points;

[0062] The image processing module is used to respectively perform meteorological disturbance removal processing on each of the imaging radar images according to the meteorological correction triangular network to form a plurality of processed imaging radar images;

[0063] The image interference module is used to obtain the phase difference data of the target electric tower by using differential interferometry in a plurality of the processed imaging radar images;

[0064] The deformation analysis module is used to perform displacement analysis on the phase difference data of the target electric tower, calculate the surface deformation phase difference of the target electric tower, and determine the deformation degree of the target electric tower according to the surface deformation phase difference.

[0065] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0066] The present invention provides a method for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors. By setting corner reflectors on the target electric tower, the reflection of the GB-SAR signal can be enhanced when the GB-SAR device acquires and forms radar images, enabling continuous image acquisition and improving the accuracy and stability of the radar images. After obtaining multiple radar images, by comparing all the radar images, candidate pixel points that exist in all the radar images can be determined. Calculate the coherence coefficient and amplitude dispersion index of these candidate pixel points, and screen out the PSC points. Based on these PSC points, a meteorological correction triangular network covering the target monitoring area can be constructed to perform meteorological disturbance removal processing on each radar image to form a processed radar image, thereby eliminating the influence of environmental factors in the radar image and improving the image accuracy. Using differential interferometry technology, more accurate phase difference data of the target electric tower can be obtained in the processed radar image. By performing displacement analysis on the phase difference data of the target electric tower, the surface deformation phase difference of the target electric tower can be obtained, and then the deformation degree of the target electric tower can be accurately obtained, improving the accuracy of electric tower monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 It is a schematic flowchart of an embodiment of the method for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors provided by the present invention;

[0068] Figure 2 It is a schematic flowchart of an embodiment of the method for acquiring radar images based on a GB-SAR device provided by the present invention;

[0069] Figure 3 It is a schematic diagram of a radar image acquisition provided by the present invention;

[0070] Figure 4 It is a schematic diagram of a displacement monitoring method provided by the present invention;

[0071] Figure 5 It is a schematic structural diagram of an embodiment of the device for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0072] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0073] The flowcharts shown in the accompanying drawings are only illustrative examples and do not necessarily include all content and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can be decomposed, combined, or partially merged, so the actual execution order may change according to the actual situation.

[0074] The following will describe in detail some embodiments of the present invention with reference to the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0075] Embodiment 1

[0076] As Figure 1 shown, it is a schematic flowchart of an embodiment of the method for monitoring the deformation of an electric tower based on GB - SAR and corner reflectors provided by the present invention. The method includes steps 101 to 107, and the specific steps are as follows:

[0077] Step 101: Use a GB - SAR device to collect a plurality of imaging radar images of the target monitoring area where the target electric tower is located; wherein, a plurality of corner reflectors are arranged on the target electric tower.

[0078] In the embodiment of the present invention, to monitor the deformation degree of the target electric tower, a GB - SAR (Ground - based Synthetic Aperture Radar) device can be used to collect imaging radar images of the target monitoring area where the target electric tower is located. Among them, to ensure that the GB - SAR device is in a stable working environment, it is necessary to analyze the deployment location of the GB - SAR device. The GB - SAR device needs to be deployed on a stable ground surface within a certain range from the target electric tower to ensure that the scanning range of the GB - SAR device can fully cover the target electric tower. Specifically, the deployment location of the GB - SAR device needs to be able to clearly see the location of the monitoring target to avoid line - of - sight occlusion. At the same time, consider the terrain and geological stability to ensure the stability and safety of the monitoring device, ensure that the base of the GB - SAR device is stable, and prevent the monitoring results from being affected by ground vibration or settlement. In addition, to improve the azimuth resolution of the imaging radar images collected by the GB - SAR device, the GB - SAR device can be installed on a linear guide for repeat - orbit observation, and a relatively corresponding calculation method is used to synthesize a small - size real - aperture into a larger - size signal antenna to transmit microwaves and receive echoes, thereby generating two - dimensional (range and azimuth angle) imaging radar images.

[0079] In an embodiment of the present invention, a plurality of corner reflectors are arranged on the target electric tower. In order to ensure that accurate deformation data of the target electric tower can be obtained, corner reflectors can be installed at key parts of the target electric tower (such as the tower base, the tower body connection, etc.) to ensure that the transmission tower line system has the characteristics of being tall and flexible, and its geometric nonlinear characteristics cannot be ignored. Since the deformation of the target electric tower is not only due to the changes in its structure itself, but also to a large extent affected by the geological activities around the tower base. Therefore, it is also very important to monitor the deformation of the surface around the tower base. The transmission line towers erected in the suburbs or even in the mountains are usually covered with dense vegetation around their tower bases. The presence of vegetation often causes the radar's backscattered signal to lose coherence, making it impossible to perform interference calculation on the imaging radar image to obtain accurate electric tower deformation data. Therefore, laying corner reflectors on the target electric tower can effectively enhance the reflection of GB-SAR signals, realize continuous image acquisition, and improve the accuracy and stability of imaging radar images.

[0080] In an embodiment of the present invention, a GB-SAR device is used to collect a number of imaging radar images of the target monitoring area where the target tower is located. The data collection interval can be adjusted according to actual needs, and the minimum interval can be as low as seconds, so as to minimize the problems caused by phase unwrapping and capture faster changes and deformations.

[0081] As an example of an embodiment of the present invention, see Figure 2 , is a flow chart of an embodiment of an imaging radar image acquisition method based on a GB-SAR device provided by the present invention. When monitoring the deformation degree of a target power tower, the GB-SAR device acquires an imaging radar image of a target monitoring area where the target power tower is located to form raw data, which includes the x-coordinate, y-coordinate, amplitude information and phase information of the target power tower. Among them, the amplitude information plays a key role in analyzing the image scene and studying the backscattering properties of the monitored area, while the phase information can be used for deformation monitoring or building a digital elevation model.

[0082] As an example of an embodiment of the present invention, see Figure 3 , is a schematic diagram of imaging radar image acquisition provided by the present invention. Figure 3 The area to be tested is the target monitoring area where the target tower is located. The synthetic antenna of GB-SAR is set on a ground-based SAR sliding track at a certain height above the ground. It moves at equal intervals and at a uniform speed on the carrier platform and transmits frequency-modulated microwave signals. The synthetic antenna then receives the signal reflected from the area to be tested. After the radar system adjusts and processes the reflected signal, a two-dimensional imaging radar image of the area to be tested can be obtained, which includes range data and azimuth data.

[0083] In the embodiments of the present invention, since meteorological factors have a great impact on the accuracy of ground-based SAR time-series deformation monitoring, in order to ensure the reliability of the imaging radar images collected by the GB-SAR device, meteorological correction needs to be performed on the imaging radar images. Therefore, after the imaging radar images are collected and before processing using differential interferometry, the imaging radar images can be first processed to remove meteorological disturbances, and more accurate deformation data can be obtained when the imaging radar images are processed subsequently. The process of removing meteorological disturbances from the imaging radar images is described through the following steps 102 - 105.

[0084] Step 102: Compare and analyze each of the imaging radar images, and take the pixel points that exist in all of the imaging radar images as candidate pixel points.

[0085] In the embodiments of the present invention, due to the diversity and complexity of the atmospheric influence, there are various meteorological correction methods. Considering the characteristics of the foundation pit monitoring area, such as small range, gentle spatial variation, small slope deformation amount, and continuous image time series, the PSC (Persistent Scatterer Candidates) network can be used to perform meteorological correction on the imaging radar images in this embodiment.

[0086] In the embodiments of the present invention, when using the PSC network to perform meteorological correction on the imaging radar images, it is first necessary to determine the PSC points. The PSC points are screened from all the pixel points in the imaging radar images. Therefore, to ensure that the selected PSC points can cover the target monitoring area, it is necessary to first perform a preliminary screening on the pixel points on the imaging radar images. Specifically, compare and analyze multiple collected imaging radar images, and through the comparison results, screen out the pixel points that exist in all of the imaging radar images and determine them as candidate pixel points. In subsequent processing, the PSC points can be screened from the candidate pixel points.

[0087] Step 103: Select PSC points from each of the candidate pixel points by calculating the coherence coefficient and amplitude dispersion index of each of the candidate pixel points.

[0088] As a preferred solution of this embodiment, selecting PSC points from each of the candidate pixel points by calculating the coherence coefficient and amplitude dispersion index of each of the candidate pixel points includes:

[0089] Select PS points from each of the candidate pixel points by calculating the coherence coefficient of each of the candidate pixel points;

[0090] Select PSC points from each of the PS points by calculating the amplitude dispersion index of each of the PS points.

[0091] In an embodiment of the present invention, after determining the candidate pixel points, PSC points are selected from the candidate pixel points. The process may be to first calculate the coherence coefficient of each candidate pixel point, and based on the calculation result of the coherence coefficient, permanent scatterers that have strong backscattering of radar waves and are relatively stable in time series are screened out from multiple candidate pixel points, that is, PS (Persistent Scatterer) points. PS points can maintain stable reflection characteristics in multiple radar observations. After screening out the PS points, the amplitude dispersion index of each PS point is calculated, and based on the calculation result of the amplitude dispersion index, the PS points are screened more carefully, and more stable points are selected as persistent scatterers, that is, PSC (Persistent Scatterer Candidates) points.

[0092] As a preferred solution of this embodiment, by calculating the coherence coefficient of each of the candidate pixel points, selecting PS points from each of the candidate pixel points includes:

[0093] The coherence coefficient of each of the candidate pixel points is calculated by the following formula:

[0094]

[0095] In the formula, γ n is the coherence coefficient of the nth candidate pixel point; E{·} is the expected value operator; z1 and z2 are the complex values of two adjacent imaging radar images respectively; is the complex conjugate of z2; |·| is the absolute value operator;

[0096] The mean value of the coherence coefficients is calculated based on the coherence coefficients of each of the candidate pixel points;

[0097] The candidate pixel points with a coherence coefficient greater than the mean value of the coherence coefficients are determined as PS points.

[0098] In an embodiment of the present invention, by calculating the coherence coefficient of each candidate pixel point to select PS points, specifically, the coherence coefficient of each candidate pixel point is calculated separately according to the above formula, the mean value of the coherence coefficients is calculated based on the coherence coefficients of all candidate pixel points, the coherence coefficient of each candidate pixel point and the mean value of the coherence coefficients are compared in size respectively, and the candidate pixel points with a coherence coefficient greater than the mean value of the coherence coefficients are determined as PS points. Among them, when calculating the coherence coefficient of each candidate pixel point, all imaging radar images are required, and by statistically multiplying the complex values of two adjacent imaging radar images, the coherence coefficient of each candidate pixel point can be accurately calculated.

[0099] As a preferred solution of this embodiment, by calculating the amplitude dispersion index of each of the PS points, selecting PSC points from each of the PS points includes:

[0100] Calculate the amplitude discrete index of each of the PS points through the following formula, specifically:

[0101]

[0102] In the formula, D a,ps is the amplitude discrete index of the PS point; σ a,ps is the amplitude standard deviation of the PS point; m a,ps is the average amplitude of the PS point.

[0103] Obtain a preset amplitude discrete index threshold.

[0104] Determine the PS points with an amplitude discrete index less than the preset amplitude discrete index threshold as PSC points.

[0105] In the embodiments of the present invention, PSC points are selected by calculating the amplitude discrete index of each PS point. Specifically, the amplitude discrete index of each PS point is calculated respectively according to the above formula; a preset amplitude discrete index threshold is obtained, and this threshold is usually selected according to experience; the amplitude discrete index of each PS point is compared with the preset amplitude discrete index threshold respectively, and the PS points with an amplitude discrete index less than the preset amplitude discrete index threshold are screened out, and these more stable PS points are determined as PSC points.

[0106] Step 104: Based on each of the PSC points, construct a meteorological correction triangular network covering the target monitoring area.

[0107] In the embodiments of the present invention, after screening out the PSC points, a meteorological correction triangular network is constructed according to these PSC points. This meteorological correction triangular network needs to cover the entire target monitoring area for atmospheric influence correction.

[0108] Step 105: According to the meteorological correction triangular network, perform meteorological disturbance removal processing on each of the imaging radar images to form a plurality of processed imaging radar images.

[0109] As a preferred solution of this embodiment, according to the meteorological correction triangular network, perform meteorological disturbance removal processing on each of the imaging radar images to form a plurality of processed imaging radar images, including:

[0110] For each pixel point in the imaging radar image, determine the triangle in the meteorological correction triangular network where the pixel point is located;

[0111] Calculate the distance data between the pixel point and a plurality of PSC points in the triangle respectively;

[0112] Determine the weight of the pixel point according to the distance data;

[0113] Perform weighted correction on the pixel points according to the weights to form a processed imaging radar image.

[0114] In an embodiment of the present invention, a meteorological correction triangular network is used to perform meteorological disturbance removal processing on an imaging radar image. Specifically: for each pixel point in the imaging radar image, first determine the triangle in which it is located in the meteorological correction triangular network, determine the weight of the pixel point by calculating the distances between the pixel point and each PSC point in the triangle where it is located, and apply these weights to perform weighted correction on the pixel point, which can eliminate the influence of the atmosphere and form a processed imaging radar image.

[0115] Step 106: Adopt differential interferometric measurement technology to obtain the phase difference data of the target electric tower in a plurality of the processed imaging radar images.

[0116] As an example of an embodiment of the present invention, see Figure 4 , which is a schematic diagram of a displacement monitoring method provided by the present invention. The GB-SAR device emits a microwave signal at time t1 to reach point P in the target monitoring area. After the antenna receives the echo signal of point P and stores the information, the distance ρ1 between the radar and point P of the position information of point P is obtained; at time t2, the process of time t1 is repeated to obtain the distance ρ2 between the radar and point P of the position information of point P. Then this process can be described as: ′ point position information radar and P ′ point distance ρ2, then this process can be described as:

[0117]

[0118] In the formula, Δφ is the phase difference between point P and point P ′ ; λ is the wavelength of the microwave signal emitted by the GB-SAR device; Δρ is the displacement change amount between point P and point P ′ point.

[0119] In an embodiment of the present invention, to calculate the displacement change amount of the target electric tower in the target monitoring area, it is necessary to first calculate the phase difference of the target electric tower. In the embodiment of the present invention, through differential interferometric measurement technology to process the processed imaging radar image, the phase difference data of the target electric can be accurately measured.

[0120] As a preferred solution of this embodiment, adopting differential interferometric measurement technology to obtain the phase difference data of the target electric tower in a plurality of the processed imaging radar images includes:

[0121] Based on differential interferometric measurement technology, perform pixel co-multiplication processing on two adjacent processed imaging radar images to obtain a plurality of interferometric phase images;

[0122] Respectively determine the target pixel points corresponding to the target electric tower in each of the interferometric phase images;

[0123] Obtain the phase difference of the target pixel point in each of the interference phase images respectively;

[0124] Determine the phase difference data of the target electric tower by taking the phase differences of all the target pixel points;

[0125] Among them, obtaining the phase difference of the target pixel point in each of the interference phase images respectively through the following formula includes:

[0126]

[0127] In the formula, Δφ(P) is the phase difference of the target pixel point P; I1(P) and I2(P) are the complex values of two interference phase images respectively; is the complex conjugate of I1(P); ∠(·) is the phase angle operator; φ1(P) is the phase of the target pixel point P in I1(P); φ2(P) is the phase of the target pixel point P in I2(P).

[0128] In the embodiment of the present invention, for the target electric tower, after collecting the imaging radar images of the target monitoring area where the target electric tower is located at different acquisition times, the differential interferometric measurement technology is used to analyze the two imaging radar images to obtain the interference phase image, and the phase difference data of the target electric tower can be obtained in the interference phase image. For example, the imaging radar images collected at two different acquisition times are I1 and I2 respectively. After performing the element-wise multiplication process on I1 and I2, that is, obtaining Obtain the phase angle of, and then the phase difference data of the target electric tower can be obtained. Among them, the phase difference data of the target electric tower is the phase difference of the target electric tower on the two imaging radar images.

[0129] In the embodiment of the present invention, assuming that after collecting the imaging radar images of the target monitoring area where the target electric tower is located at two different acquisition times, the phases φ1(P) and φ2(P) of the target electric tower can be obtained on the two images respectively:

[0130]

[0131] In the formula, R1 and R2 are the distances between the GB-SAR device and the target electric tower at different acquisition times respectively; λ is the wavelength of the microwave signal emitted by the GB-SAR device; and are the phase changes generated when the radar signal propagates respectively.

[0132] Therefore, the interferometric measurement phase Δφ(P) observed by the GB-SAR device is:

[0133]

[0134] Furthermore, when the time change is sufficient, the phase change generated during the propagation of the radar signal and remain unchanged. Therefore, the phase difference Δφ(P) directly reflects the distance difference between the two observation positions (R2 and R1) of the target electric tower, and this distance difference is actually the displacement information of the target electric tower. However, in actual situations, since the phase shift component will change, the interferometric phase Δφ(P) needs to consider the following factors, expressed as:

[0135]

[0136] In the formula, is the phase shift caused by the deformation of the ground surface in the radar line of sight; is the phase shift caused by meteorological disturbances; is the phase shift caused by orbit errors; is the phase shift caused by the spatial baseline; is the phase shift caused by noise; n is the integer ambiguity.

[0137] Since the GB-SAR device performs continuous observations under extremely stable orbits, during the image acquisition process, the phase differences caused by orbit errors and the spatial baseline are small enough to be negligible. Therefore, the phase difference caused by the deformation of the ground surface in the radar line of sight can be expressed as:

[0138]

[0139] Since the meteorological disturbance influencing factors have been removed from the imaging radar image before performing differential interferometry, so can be expressed as:

[0140] As a preferred solution of this embodiment, for the phase shift caused by noise, before performing differential interferometry, the imaging radar image can be denoised first. After using the GB-SAR device to collect several imaging radar images of the target monitoring area where the target electric tower is located, it further includes:

[0141] For each imaging radar image, determine the phase vectors of all pixel points in the imaging radar image;

[0142] Sum up the phase vectors of all the pixel points to obtain the main vector;

[0143] Calculate several phase angle differences between all the pixel points and the main vector respectively;

[0144] Determine the median of the phase differences among several of the phase angle differences;

[0145] Based on the median of the phase differences, determine the phase difference weights corresponding to each of the phase angle differences;

[0146] Perform weighted summation processing according to several of the phase angle differences and the phase difference weights corresponding to each of the phase angle differences to obtain a summation result;

[0147] According to the summation result and the phase angle of the main vector corresponding to the main vector, obtain an imaging radar image with noise removed.

[0148] In the embodiments of the present invention, due to the discontinuity of the target monitoring area, the problem of overlapping signal and noise frequency bands in the interference phase diagram will occur. Therefore, the circular weighted median smoothing algorithm is adopted in this embodiment to remove both the thermal noise and environmental noise of the imaging radar image. Specifically, the main vector d is obtained using the following formula n,m :

[0149]

[0150] In the formula, d n,m is the main vector; (kn, km) are the coordinates of the pixel point in the imaging radar image; is the phase vector of the pixel point; n and m respectively represent the position coordinates of the pixel point in its row and column; N and M are used to determine the size of the neighborhood range considered during the filtering operation. For example, when N = 2 and M = 2, the filtering window will include an area of 2 pixels on each side around the current position, forming a 5x5 window (including the central pixel) in total.

[0151] Furthermore, use the following formula to calculate the phase angle difference between each pixel point in the imaging radar image and the main vector d n,m :

[0152]

[0153] In the formula, is the phase angle difference between the pixel point and the main vector; arg[·] represents the operation of finding the phase angle of a complex number; is the phase vector of the pixel point; d n,m is the main vector.

[0154] Furthermore, use the following formula to calculate the median of the phase differences M n,m :

[0155]

[0156] In the formula, M n,mis the median of the phase difference; median[·] represents the median operation; arg[·] represents the phase angle operation on a complex number; is the phase angle difference between the pixel point and the main vector; d n,m is the main vector.

[0157] Furthermore, based on the median of the phase difference M n,m , the following formula is used to calculate the phase angle difference corresponding to each phase difference weight value W kn,km :

[0158]

[0159] In the formula, W kn,km is the phase difference weight value; is the phase angle difference between the pixel point and the main vector; M n,m is the median of the phase difference; S n,m is the phase weighted value of the pixel point.

[0160] Among them, S n,m is calculated using the following formula:

[0161]

[0162] In the formula, S n,m is the phase weighted value of the pixel point; is the phase angle difference between the pixel point and the main vector; M n,m is the median of the phase difference.

[0163] Furthermore, after obtaining the phase difference weight values corresponding to the phase angle differences of each pixel point, the following formula is used to obtain the result after noise filtering:

[0164]

[0165] In the formula, is the phase difference of the pixel point after noise filtering; W kn,km is the phase difference weight value; is the phase angle difference between the pixel point and the main vector; arg[·] represents the phase angle operation on a complex number; d n,m is the main vector.

[0166] Therefore, after the imaging radar image removes the noise influencing factors and undergoes differential interferometric measurement processing to form an interferometric phase image, it can be expressed as:

[0167] Step 107: By performing displacement analysis on the phase difference data of the target electric tower, calculate the surface deformation phase difference of the target electric tower, and determine the deformation degree of the target electric tower according to the surface deformation phase difference.

[0168] As a preferred solution of this embodiment, by performing displacement analysis on the phase difference data of the target electric tower, the surface deformation phase difference of the target electric tower is calculated, and the deformation degree of the target electric tower is determined according to the surface deformation phase difference, including:

[0169] By performing displacement analysis on the phase difference data of the target electric tower, the phase change law of the target electric tower is determined;

[0170] According to the phase change law of the target electric tower, the integer ambiguity is calculated;

[0171] According to the phase difference data of the target electric tower and the integer ambiguity, the surface deformation phase difference of the target electric tower is calculated;

[0172] According to the surface deformation phase difference of the target electric tower, the deformation degree of the target electric tower is determined.

[0173] As a preferred solution of this embodiment, according to the phase difference data of the target electric tower and the integer ambiguity, the surface deformation phase difference of the target electric tower is calculated, including:

[0174]

[0175] In the formula, is the surface deformation phase difference of the target electric tower; Δφ(P) is the phase difference of the target pixel point P; n is the integer ambiguity.

[0176] In the embodiment of the present invention, since is to calculate the surface deformation phase difference of the target electric tower it is necessary to calculate the integer ambiguity n. Usually, the integer ambiguity can be restored by phase unwrapping technology. Among them, the phase change law in the time series can be used to infer the integer ambiguity n. Therefore, by performing displacement analysis on the phase difference data of the target electric tower, the phase change law of the target electric tower can be determined, and then the integer ambiguity n can be inferred, and then the formula is used to calculate the surface deformation phase difference of the target electric tower. After calculating the surface deformation phase difference of the target electric tower, the deformation degree of the target electric tower with high precision can be determined.

[0177] In the embodiment of the present invention, after determining the deformation degree of the target electric tower, a deformation threshold of the target electric tower can be preset. When it is monitored that the deformation degree of the target electric tower reaches or exceeds the preset deformation threshold, the early warning mechanism is automatically triggered, and alarm information is sent through communication means such as text messages and emails to timely feedback and respond to the abnormal deformation of the electric tower and ensure the safety of the power grid.

[0178] Implementing the above embodiments has the following effects:

[0179] The present invention provides a method for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors. By setting corner reflectors on the target electric tower, the reflection of GB-SAR signals can be enhanced when the GB-SAR device acquires imaging radar images, enabling continuous image acquisition and improving the accuracy and stability of the imaging radar images. After obtaining multiple imaging radar images, by comparing all the imaging radar images, candidate pixel points that exist in all the imaging radar images can be determined. The coherence coefficient and amplitude dispersion index of these candidate pixel points are calculated, and PSC points are screened out. Based on these PSC points, a meteorological correction triangular network covering the target monitoring area can be constructed to perform meteorological disturbance removal processing on each imaging radar image to form processed imaging radar images, thereby eliminating the influence of environmental factors in the imaging radar images and improving image accuracy. By using differential interferometry, more accurate phase difference data of the target electric tower can be obtained in the processed imaging radar images. Through displacement analysis of the phase difference data of the target electric tower, the surface deformation phase difference of the target electric tower can be obtained, and then the deformation degree of the target electric tower can be accurately obtained, improving the accuracy of electric tower monitoring.

[0180] Embodiment 2

[0181] See Figure 5 , which is a schematic structural diagram of an embodiment of the device for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors provided by the present invention. The device includes: a data acquisition module, a first screening module, a second screening module, a construction module, an image processing module, an image interference module, and a deformation analysis module;

[0182] The data acquisition module is used to respectively acquire a plurality of imaging radar images of the target monitoring area where the target electric tower is located by using a GB-SAR device; wherein, a plurality of corner reflectors are arranged on the target electric tower;

[0183] The first screening module is used to perform comparative analysis on each of the imaging radar images and use the pixel points that exist in all the imaging radar images as candidate pixel points;

[0184] The second screening module is used to select PSC points from each of the candidate pixel points by calculating the coherence coefficient and amplitude dispersion index of each of the candidate pixel points;

[0185] The construction module is used to construct a meteorological correction triangular network covering the target monitoring area based on each of the PSC points;

[0186] The image processing module is used to respectively perform meteorological disturbance removal processing on each of the imaging radar images according to the meteorological correction triangular network to form a plurality of processed imaging radar images;

[0187] The image interference module is used to obtain the phase difference data of the target electric tower in several of the processed imaging radar images by using differential interferometry measurement technology;

[0188] The deformation analysis module is used to calculate the surface deformation phase difference of the target electric tower by performing displacement analysis on the phase difference data of the target electric tower, and determine the deformation degree of the target electric tower according to the surface deformation phase difference.

[0189] As a preferred solution of this embodiment, by calculating the coherence coefficient and amplitude dispersion index of each of the candidate pixel points, the PSC points are selected from each of the candidate pixel points, including:

[0190] By calculating the coherence coefficient of each of the candidate pixel points, the PS points are selected from each of the candidate pixel points;

[0191] By calculating the amplitude dispersion index of each of the PS points, the PSC points are selected from each of the PS points.

[0192] As a preferred solution of this embodiment, by calculating the coherence coefficient of each of the candidate pixel points, the PS points are selected from each of the candidate pixel points, including:

[0193] The coherence coefficient of each of the candidate pixel points is calculated by the following formula:

[0194]

[0195] In the formula, γ n is the coherence coefficient of the nth candidate pixel point; E{·} is the expected value operator; z1 and z2 are the complex values of two adjacent imaging radar images respectively; is the complex conjugate of z2; |·| is the absolute value operator;

[0196] The mean value of the coherence coefficients is calculated based on the coherence coefficients of each of the candidate pixel points;

[0197] The candidate pixel points with coherence coefficients greater than the mean value of the coherence coefficients are determined as PS points.

[0198] As a preferred solution of this embodiment, by calculating the amplitude dispersion index of each of the PS points, the PSC points are selected from each of the PS points, including:

[0199] The amplitude dispersion index of each of the PS points is calculated by the following formula, specifically:

[0200]

[0201] In the formula, D a,ps is the amplitude dispersion index of the PS point; σ a,ps is the amplitude standard deviation of the PS point; m a,psis the average amplitude of the PS points;

[0202] Obtain a preset amplitude dispersion index threshold;

[0203] Determine the PS points with an amplitude dispersion index less than the preset amplitude dispersion index threshold as PSC points.

[0204] As a preferred solution of this embodiment, according to the meteorological correction triangular network, perform meteorological disturbance removal processing on each of the imaging radar images to form a plurality of processed imaging radar images, including:

[0205] For each pixel point in the imaging radar image, determine the triangle where the pixel point is located in the meteorological correction triangular network;

[0206] Calculate the distance data between the pixel point and a plurality of PSC points in the triangle respectively;

[0207] Determine the weight of the pixel point according to the distance data;

[0208] Perform weighted correction on the pixel point according to the weight to form a processed imaging radar image.

[0209] As a preferred solution of this embodiment, adopt differential interferometry to obtain the phase difference data of the target electric tower in a plurality of the processed imaging radar images, including:

[0210] Based on differential interferometry, perform pixel co-multiplication processing on two adjacent processed imaging radar images to obtain a plurality of interferometric phase images;

[0211] Determine the target pixel points corresponding to the target electric tower in each of the interferometric phase images respectively;

[0212] Obtain the phase difference of the target pixel point in each of the interferometric phase images respectively;

[0213] Determine the phase difference of all the target pixel points as the phase difference data of the target electric tower;

[0214] Among them, the phase difference of the target pixel point is obtained in each of the interferometric phase images through the following formula, including:

[0215]

[0216] In the formula, Δφ(P) is the phase difference of the target pixel point P; I1(P) and I2(P) are the complex values of two interferometric phase images respectively; is the complex conjugate of I1(P); ∠(·) is the phase angle operator; φ1(P) is the phase of the target pixel point P in I1(P); φ2(P) is the phase of the target pixel point P in I2(P).

[0217] As a preferred solution of this embodiment, by performing displacement analysis on the phase difference data of the target electric tower, the surface deformation phase difference of the target electric tower is calculated, and the deformation degree of the target electric tower is determined according to the surface deformation phase difference, including:

[0218] By performing displacement analysis on the phase difference data of the target electric tower, the phase change law of the target electric tower is determined;

[0219] The integer ambiguity is calculated according to the phase change law of the target electric tower;

[0220] According to the phase difference data of the target electric tower and the integer ambiguity, the surface deformation phase difference of the target electric tower is calculated;

[0221] The deformation degree of the target electric tower is determined according to the surface deformation phase difference of the target electric tower.

[0222] As a preferred solution of this embodiment, according to the phase difference data of the target electric tower and the integer ambiguity, the surface deformation phase difference of the target electric tower is calculated, including:

[0223]

[0224] In the formula, is the surface deformation phase difference of the target electric tower; Δφ(P) is the phase difference of the target pixel point P; n is the integer ambiguity.

[0225] As a preferred solution of this embodiment, after using the GB-SAR device to collect a plurality of imaging radar images of the target monitoring area where the target electric tower is located, it further includes:

[0226] For each imaging radar image, determine the phase vectors of all pixel points in the imaging radar image;

[0227] Perform a summation process on the phase vectors of all the pixel points to obtain the main vector;

[0228] Calculate a plurality of phase angle differences between all the pixel points and the main vector respectively;

[0229] Determine the median of the phase differences among the plurality of phase angle differences;

[0230] Based on the median of the phase differences, determine the phase difference weight values corresponding to the respective phase angle differences;

[0231] Perform a weighted summation process based on a plurality of the phase angle differences and the phase difference weight values corresponding to the respective phase angle differences to obtain a summation result;

[0232] Based on the summation result and the main vector phase angle corresponding to the main vector, obtain an imaging radar image with noise removed.

[0233] Implementing the above embodiments has the following effects:

[0234] The present invention provides a deformation monitoring device for an electric tower based on GB-SAR and a corner reflector. By setting a corner reflector on the target electric tower, it can enhance the reflection of the GB-SAR signal when the GB-SAR device acquires an imaging radar image, realize continuous image acquisition, and improve the accuracy and stability of the imaging radar image; after obtaining multiple imaging radar images, by comparing all the imaging radar images, candidate pixel points that exist in all the imaging radar images can be determined, the coherence coefficient and amplitude dispersion index of these candidate pixel points are calculated, PSC points are screened out, and a meteorological correction triangular network covering the target monitoring area can be constructed based on these PSC points, so that the meteorological correction triangular network performs meteorological disturbance removal processing on each imaging radar image to form a processed imaging radar image, thereby eliminating the influence of environmental factors in the imaging radar image and improving the image accuracy; by using differential interferometry, more accurate phase difference data of the target electric tower can be obtained in the processed imaging radar image; displacement analysis of the phase difference data of the target electric tower can obtain the surface deformation phase difference of the target electric tower, and then accurately obtain the deformation degree of the target electric tower, improving the accuracy of electric tower monitoring.

[0235] The above specific embodiments have further elaborated on the purpose, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. In particular, it is pointed out that for those skilled in the art, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A deformation monitoring method for electric towers based on GB-SAR and corner reflectors, characterized in that Including: Using a GB-SAR device to collect a plurality of imaging radar images of a target monitoring area where a target electric tower is located; wherein, a plurality of corner reflectors are arranged on the target electric tower; Comparatively analyzing each of the imaging radar images, and taking the pixel points that exist in all of the imaging radar images simultaneously as candidate pixel points; Selecting PSC points from among the candidate pixel points by calculating the coherence coefficient and amplitude dispersion index of each of the candidate pixel points; Based on each of the PSC points, constructing a meteorological correction triangular network covering the target monitoring area; According to the meteorological correction triangular network, respectively performing meteorological disturbance removal processing on each of the imaging radar images to form a plurality of processed imaging radar images; Adopting differential interferometry to obtain the phase difference data of the target electric tower from among the plurality of processed imaging radar images; By performing displacement analysis on the phase difference data of the target electric tower, calculating the surface deformation phase difference of the target electric tower, and determining the deformation degree of the target electric tower according to the surface deformation phase difference.

2. The method for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors according to claim 1, wherein The step of selecting PSC points from among the candidate pixel points by calculating the coherence coefficient and amplitude dispersion index of each of the candidate pixel points includes: Selecting PS points from among the candidate pixel points by calculating the coherence coefficient of each of the candidate pixel points; Selecting PSC points from among the PS points by calculating the amplitude dispersion index of each of the PS points.

3. The method for monitoring the deformation of an electric tower based on GB-SAR and a corner reflector according to claim 2, wherein The step of selecting PS points from among the candidate pixel points by calculating the coherence coefficient of each of the candidate pixel points includes: Calculating the coherence coefficient of each of the candidate pixel points through the following formula: where γ n is the coherence coefficient of the nth candidate pixel point; E{·} is the expected value operator; z1 and z2 are the complex values of two adjacent imaging radar images respectively; is the complex conjugate of z2; |·| is the absolute value operator; Calculating the mean value of the coherence coefficients according to the coherence coefficients of each of the candidate pixel points; Determining the candidate pixel points with a coherence coefficient greater than the mean value of the coherence coefficients as PS points.

4. The method for monitoring the deformation of an electric tower based on GB-SAR and a corner reflector according to claim 2, wherein The step of selecting PSC points from among the PS points by calculating the amplitude dispersion index of each of the PS points includes: Calculating the amplitude dispersion index of each of the PS points through the following formula, specifically: where D a,ps is the amplitude discrete index of the PS points; σ a,ps is the amplitude standard deviation of the PS points; m a,ps is the average amplitude of the PS points; Obtaining a preset amplitude dispersion index threshold; Determining the PS points with an amplitude dispersion index less than the preset amplitude dispersion index threshold as PSC points.

5. The method for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors according to claim 1, characterized in that, The step of respectively performing meteorological disturbance removal processing on each of the imaging radar images according to the meteorological correction triangular network to form a plurality of processed imaging radar images includes: For each pixel point in the imaging radar image, determining the triangle in the meteorological correction triangular network where the pixel point is located; Respectively calculating the distance data between the pixel point and a plurality of PSC points in the triangle; Determining the weight of the pixel point according to the distance data; Performing weighted correction on the pixel point according to the weight to form a processed imaging radar image.

6. The method for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors according to claim 1, wherein The step of adopting differential interferometry to obtain the phase difference data of the target electric tower from among the plurality of processed imaging radar images includes: Based on differential interferometry, performing pixel co-multiplication processing on two adjacent processed imaging radar images to obtain a plurality of interference phase images; Respectively determining the target pixel points corresponding to the target electric tower in each of the interference phase images; Obtain the phase differences of the target pixel points in each of the interference phase images respectively; Determine the phase difference data of the target electric tower based on the phase differences of all the target pixel points; Among them, obtaining the phase differences of the target pixel points in each of the interference phase images through the following formula includes: Where, Δφ(P) is the phase difference of the target pixel point P; I1(P) and I2(P) are the complex values of two interference phase images respectively; is the complex conjugate of I1(P); ∠(·) is the phase angle operator; φ1(P) is the phase of the target pixel point P in I1(P); φ2(P) is the phase of the target pixel point P in I2(P).

7. The method for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors according to claim 6, wherein By performing displacement analysis on the phase difference data of the target electric tower, calculating the surface deformation phase difference of the target electric tower, and determining the deformation degree of the target electric tower according to the surface deformation phase difference, includes: Determine the phase change law of the target electric tower by performing displacement analysis on the phase difference data of the target electric tower; Calculate the integer ambiguity according to the phase change law of the target electric tower; Calculate the surface deformation phase difference of the target electric tower based on the phase difference data of the target electric tower and the integer ambiguity; Determine the deformation degree of the target electric tower according to the surface deformation phase difference of the target electric tower.

8. The method for monitoring the deformation of an electric tower based on GB-SAR and a corner reflector according to claim 7, wherein The calculating the surface deformation phase difference of the target electric tower based on the phase difference data of the target electric tower and the integer ambiguity includes: In the formula, is the surface deformation phase difference of the target electric tower; Δφ(P) is the phase difference of the target pixel point P; n is the integer ambiguity.

9. The method for monitoring the deformation of an electric tower based on GB-SAR and corner reflectors according to claim 1, characterized in that After using the GB-SAR device to respectively collect a plurality of imaging radar images of the target monitoring area where the target electric tower is located, it further includes: For each imaging radar image, determine the phase vectors of all pixel points in the imaging radar image; Perform a summation process on the phase vectors of all the pixel points to obtain the main vector; Calculate a plurality of phase angle differences between all the pixel points and the main vector respectively; Determine the median of the phase differences among the plurality of phase angle differences; Based on the median of the phase differences, determine the phase difference weights corresponding to each of the phase angle differences; Perform a weighted summation process according to the plurality of phase angle differences and the phase difference weights corresponding to each of the phase angle differences to obtain a summation result; Obtain the imaging radar image with noise removed according to the summation result and the main vector phase angle corresponding to the main vector.

10. A deformation monitoring device for electric towers based on GB-SAR and corner reflectors, characterized in that, Includes: A data acquisition module, a first screening module, a second screening module, a construction module, an image processing module, an image interference module, and a deformation analysis module; The data acquisition module is used to respectively collect a plurality of imaging radar images of the target monitoring area where the target electric tower is located by using the GB-SAR device; wherein, a plurality of corner reflectors are arranged on the target electric tower; The first screening module is used to perform a comparative analysis on each of the imaging radar images, and take the pixel points that exist in all the imaging radar images simultaneously as candidate pixel points; The second screening module is used to select PSC points among the candidate pixel points by calculating the coherence coefficient and amplitude discrete index of each of the candidate pixel points; The construction module is used to construct a meteorological correction triangular network covering the target monitoring area based on each of the PSC points; The image processing module is used to respectively perform meteorological disturbance removal processing on each of the imaging radar images according to the meteorological correction triangular network to form a plurality of processed imaging radar images; The image interference module is used to obtain the phase difference data of the target electric tower in a plurality of the processed imaging radar images by using differential interferometry measurement technology; The deformation analysis module is used to calculate the ground deformation phase difference of the target electric tower by performing displacement analysis on the phase difference data of the target electric tower, and determine the deformation degree of the target electric tower according to the ground deformation phase difference.

Images