A PS-InSAR-based method for monitoring surface deformation along subway lines

Abstract

This invention provides a method for monitoring surface deformation along subway lines based on PS-InSAR. The method includes: acquiring multiple SAR images of monitoring points along the subway line; preprocessing each SAR image and stitching them together to generate multiple sets of whole-scene SLC images; performing registration and interferometric processing on the multiple sets of whole-scene SLC images to obtain a first interferometric atlas; obtaining a second interferometric atlas based on the first interferometric atlas; selecting coherence points based on the second interferometric atlas, establishing a deformation model, and calculating the deformation rate and height of each monitoring point; obtaining the surface deformation hazard value based on the deformation rate, and obtaining ground subsidence information and building deformation information based on the height, thereby realizing the monitoring of surface deformation along the subway line. This invention can achieve rapid and accurate classification of surface deformation along subway lines, improve the accuracy of surface deformation monitoring along subway lines, and is more conducive to analyzing the causes of subway line subsidence and locating risk areas.

Description

Technical Field

[0001] This invention relates to the field of surface deformation analysis technology, specifically to a method for monitoring surface deformation along subway lines based on PS-InSAR. Background Technology

[0002] Subway rail transit is the main artery of urban public transportation, the lifeline of the city, and has permeated all areas of the national economy and people's lives. With the formation and development of my country's subway rail transit network, how to scientifically survey and maintain such a large-scale subway operation line and ensure the stability and reliability of the infrastructure is a major problem that subway rail transit development must face and solve at this stage.

[0003] Currently, safety surveying for subway track engineering mainly relies on ground-based surveying methods, such as leveling, total stations, and GPS. However, while these ground-based surveying technologies offer high accuracy, they typically involve a limited number of survey points, require significant manpower and resources, and have low spatial resolution, making it difficult to meet the demands of modern disaster prevention and mitigation efforts for rapid and large-area surveying of subway track engineering projects.

[0004] In particular, many subway lines are located in complex areas with diverse structures. Facilities such as buildings, roads, and viaducts can easily obscure underground deformations. Surveyors often find it difficult to access these complex areas, hindering various tasks such as surveying and design, topographic surveying, and deformation monitoring. It also makes it impossible to accurately monitor the deformation rate of the ground along the subway line, resulting in inaccurate analysis of the causes of ground subsidence and risk location. Consequently, problems related to ground deformation along the subway line cannot be identified, creating potential hazards. Summary of the Invention

[0005] This invention provides a PS-InSAR-based method for monitoring surface deformation along subway lines, which solves the problem of inaccurate causal analysis caused by low accuracy in existing technologies for monitoring surface deformation rates along subway lines.

[0006] This invention provides a method for monitoring surface deformation along a subway line based on PS-InSAR, the method comprising:

[0007] Multiple SAR images of monitoring points along the subway line were collected, and each SAR image was preprocessed and stitched together to generate multiple sets of full-scene SLC images.

[0008] The first interferogram set is obtained by performing registration and interferometric processing on multiple sets of the whole-scene SLC images; a second interferogram set is obtained based on the first interferogram set.

[0009] Based on the second interferogram set, coherent points are selected, a deformation model is established, and the deformation rate and height of each monitoring point are calculated.

[0010] Based on the deformation rate, determine whether the current monitoring point is a dangerous point; obtain the total number of monitoring points and the number of dangerous points between multiple subway stations, and calculate the surface deformation hazard value; classify the monitoring points based on the height to obtain ground settlement information and building deformation information respectively;

[0011] Based on surface deformation hazard values, ground subsidence information, and building deformation information, deformation monitoring of the surface along the subway line can be achieved.

[0012] Furthermore, the preprocessing includes: range and azimuth spectrum estimation of the SAR image, range compression, azimuth pre-filtering, azimuth autofocus and compression, and multi-view processing.

[0013] Furthermore, the SAR image is in Raw format.

[0014] Furthermore, the registration and interference processes include:

[0015] A first image and multiple second images are obtained by filtering from multiple sets of whole-scene SLC images, and each second image is registered with the first image to obtain multiple corresponding third images;

[0016] Each of the third images is subjected to interference processing with each pixel in the first image to obtain the first interference set.

[0017] Furthermore, the filtering process involves sorting multiple sets of whole-scene SLC images based on pixel size, marking the whole-scene SLC image with the highest pixel count as the first image, and marking the remaining whole-scene SLC images as the second image.

[0018] Furthermore, the first interferometric atlas includes: deformation phase, terrain phase, flat terrain phase, and atmospheric phase;

[0019] The second interferogram set includes: deformation phase and atmospheric phase.

[0020] Furthermore, the coherence point is selected using the amplitude deviation index.

[0021] Furthermore, the method for determining the danger point is as follows: the deformation rate of the current monitoring point is compared with a set threshold. If it exceeds the set threshold, it is determined to be a danger point; otherwise, it is still a monitoring point.

[0022] Furthermore, the set threshold is 10 mm / year.

[0023] Furthermore, the calculation method for the surface deformation hazard value R is as follows:

[0024]

[0025] Among them, Num def N represents the total number of hazardous points across multiple subway lines; all This indicates the total number of monitoring points across multiple subway lines.

[0026] In general, the technical solution conceived by this invention can achieve the following beneficial effects compared with the prior art:

[0027] This invention provides a method for monitoring surface deformation along subway lines based on PS-InSAR. By performing a series of processes such as preprocessing, stitching, registration and interferometry on SAR images, the accuracy and precision of deformation rate and height are improved.

[0028] Secondly, the subway line is divided into sections according to the subway stations. By statistically analyzing the proportion of dangerous points in a local section to all monitoring points, the surface deformation hazard value is obtained. This is used to assess the subsidence risk between subway stations, which is helpful for analyzing the causes of subway line subsidence and locating risk areas.

[0029] Furthermore, based on monitoring points, ground monitoring points and building monitoring points are quickly classified to obtain ground settlement, building deformation, and differential deformation between the two. Combined with the hazard values ​​of the corresponding monitoring points, the causes can be quickly analyzed, achieving rapid and accurate classification of ground deformation types. This improves the monitoring accuracy and causal analysis of surface deformation along urban subway lines, and also provides data reference for subway route selection and settlement control. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0031] Figure 1 This is a schematic diagram of the method flow for monitoring surface deformation along a subway line based on PS-InSAR, provided by the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Furthermore, the technical features involved in the various embodiments described below can be combined with each other as long as they do not conflict with each other.

[0033] It should be noted that, in the description of the embodiments of the present invention, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process or method that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process or method. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, or circuit that includes said element.

[0034] like Figure 1 The diagram shown is a flowchart illustrating a method for monitoring surface deformation along a subway line based on PS-InSAR, provided by the present invention. The method includes:

[0035] Step 101: Collect multiple SAR images of monitoring points along the subway line, preprocess each SAR image, and stitch them together to generate multiple sets of full-scene SLC images.

[0036] It should be noted that SAR images are usually published in Raw format because Raw format is relatively inexpensive and can guarantee publishing speed. At the same time, Raw format data can meet different processing needs. Therefore, SAR images need to be preprocessed to generate SLC (single-view complex) images before stitching.

[0037] Multiple monitoring points are set up along the subway line. These can be placed every 5 meters or 10 meters between stations. In short, the more monitoring points there are, the more accurate the panoramic SLC image will be, and the more precise the deformation rate and height calculations for each monitoring point will be, making the analysis of the causes of deformation more convincing. Since more monitoring points lead to more accurate results, in one embodiment of this invention, more than 30 monitoring points are preferably used.

[0038] Multiple SAR images are collected from monitoring points along the subway line. That is, remote sensing data from all monitoring points along the subway line are collected at regular intervals to obtain the current period's SAR image and corresponding digital elevation model (DEM). It should be noted that the period can be one week, one month, or two months; there is no specific limitation here. The periodic SAR image collection is mainly based on the actual monitoring requirements.

[0039] Preprocessing is essentially converting Raw format data into SLC format. In one embodiment of this invention, preprocessing includes: range and azimuth spectrum estimation of the SAR image, range compression, azimuth pre-filtering, azimuth autofocus and compression, and multi-look processing.

[0040] Because the area covered in deformation monitoring of urban subway networks is quite large, and a single SAR image may not be sufficient to cover the entire monitoring area, it is necessary to preprocess all SAR images acquired concurrently before stitching them together to generate a complete SLC image. Each phase includes one complete SLC image, thereby obtaining multiple sets of complete SLC images.

[0041] Step 102: Perform registration and interferometric processing on multiple sets of full-scene SLC images to obtain the first interferogram set; obtain the second interferogram set based on the first interferogram set.

[0042] During the platform's reorbiting flight, the satellite's orbit will shift, causing the multiple sets of full-view SLC images used for interferometry to also shift to some extent. In order to obtain the optimal interferometric phase at each resolution pixel, the multiple sets of full-view SLC images need to be registered at the sub-pixel level before interferometric processing to achieve a matching effect.

[0043] That is, the registration and interferometry processes include: selecting a first image and multiple second images from multiple sets of whole-scene SLC images, registering each second image with the first image to obtain multiple corresponding third images; and performing interferometry processing on each third image with each pixel in the first image to obtain a first interferogram set.

[0044] The selection process involves sorting multiple sets of full-scene SLC images based on pixel size. The full-scene SLC image with the highest pixel count is designated as the first image, and the remaining full-scene SLC images are designated as the second images. The pixel size of the first image needs to take into account the spatial baseline, temporal baseline, and Doppler centroid frequency.

[0045] Each second image is registered with the first image to obtain multiple corresponding third images, which have subpixel-level precision.

[0046] After registration, the third image is interferometrically processed with each pixel of the first image to generate the first interferogram set, also known as the original interferogram set. Each original interferogram includes deformation phase, topographic phase, flatland phase, and atmospheric phase. The simulated flatland and topographic phases are removed from the original interferogram set using an external DEM, resulting in a deformation phase interferogram set caused by surface deformation, which is the second interferogram set. Therefore, the second interferogram set includes both deformation phase and atmospheric phase.

[0047] Step 103: Select coherent points based on the second interferogram set, establish a deformation model, and calculate the deformation rate and height of each monitoring point;

[0048] Spaceborne synthetic aperture radar interferometry (InSAR) is a satellite geodetic method with advantages such as wide coverage, high spatial resolution, all-day and all-weather operation, high precision, high degree of automation, no need for ground control points, and no need for surveyors to enter the field. It is used to monitor surface deformation caused by various geological disasters.

[0049] In this application, based on the second interferogram, the permanent scatterer (PS), which is unaffected by time and space effects, is identified by statistical analysis of the amplitude or phase information of the second interferogram, i.e., the coherent point.

[0050] As an embodiment of the present invention, the coherence point is selected by the amplitude deviation index.

[0051] The amplitude deviation index is based on the statistical relationship between amplitude deviation and phase standard deviation over a time series; that is, when the phase standard deviation... At high signal-to-noise ratios, that is, at g / σ n When the amplitude deviation is greater than 4, the amplitude deviation D A With phase standard deviation They are approximately equal, so the amplitude deviation index is used to extract the coherence points.

[0052] Since PS technology typically processes a series of individual master image interferograms directly without considering baseline limitations, the interferogram is severely affected by spatial decorrelation factors. This prevents the selection of points with high phase quality based on the spatial coherence estimation criterion. As mentioned above, under high signal-to-noise ratio conditions, the standard deviation of pixel phase... It can be approximated by the amplitude deviation D A Therefore, the amplitude deviation index can be calculated as follows:

[0053]

[0054] Where, σ A The m represents the average amplitude over time (mathematical expectation) of a pixel. A This indicates the standard deviation of the amplitude.

[0055] It should be noted that when the value of the pixel amplitude deviation index is lower than the index setting threshold, the pixel is selected as a coherent point. As an embodiment of the present invention, the index setting threshold ranges from 0.25 to 0.4.

[0056] After selecting coherent points, a deformation model is established, and the deformation rate and height of each monitoring point are calculated. Then, the second interferogram is processed to construct a coherent point network, estimate arc parameters, remove atmospheric phases, and recover deformation, ultimately obtaining the deformation rate, height, and deformation sequence of the monitoring points.

[0057] Specifically, a Deloitte triangulation network is constructed for the coherent points, and functional relationships regarding deformation, topography, and phase difference are established on the arc segments of the coherent points. Due to atmospheric delay errors, the coherent points are separated using external data or other processing methods, thereby obtaining surface deformation information at the coherent points. Since the selected coherent points have good stability over a certain period of time, deformation information from other low signal-to-noise ratio points is interpolated within these stable points to obtain the surface deformation information for the region.

[0058] It should be noted that, according to the principle of SAR interferometry, the formula for calculating the interference phase φ is: φ = φ flat +φ topo +φ def +φ aim +φ nosse ; where φ flat Indicates the flat-ground phase; φ topo Indicates the terrain phase; φ def Represents the phase component caused by settlement; φ atm Indicates atmospheric phase; φ noise This represents the phase of random noise.

[0059] After atmospheric phase removal, a deformation model is established using phase points that do not change over time. Neighboring phase points are then connected and differentially processed. Therefore, the differential interference phase φ between adjacent phase points... diff The calculation method is as follows: Where λ represents the electromagnetic wavelength; B ⊥ Represents the vertical baseline; R represents the distance between the antenna center and the target object during radar ground observation; θ represents the incident angle of the radar beam; Δh represents the elevation error increment; T represents the time baseline between the current second image and the first image; Δv represents the deformation rate increment; Δφ res Residual phase refers to atmospheric phase, nonlinear deformation phase, and random noise phase.

[0060] By establishing a deformation model that incorporates deformation and elevation error, the problem of solving for the final deformation parameters is transformed into the problem of finding the optimal solution to a nonlinear function. That is, after estimating the elevation error increment and deformation rate increment from the second interferometric dataset, the maximum optimal value of the nonlinear function is used for the solution.

[0061] The expression for a nonlinear function is: Where β represents the temporal coherence coefficient of the coherent point arc segment, and the larger the value, the smaller the model error; N represents the number of second interferograms; Δω represents the difference between the observed value and the fitted value; j represents the j-th second interferogram.

[0062] By searching in two-dimensional space, the elevation error and deformation of the corresponding coherent point arc segment are obtained. Due to the possible phase discontinuity, it is necessary to perform weighted least squares adjustment estimation on the differential increment value to obtain the deformation value and terrain residual of each monitoring point, and then calculate the deformation rate and height of each monitoring point.

[0063] It should be noted that when acquiring the deformation rate and altitude of each monitoring point, the deformation sequence is also obtained simultaneously. This involves removing the model phase from the original phase to obtain the residual temporal phase, then using spatiotemporal and spatial filtering to remove the atmospheric phase, and finally reconstructing the deformation sequence. The deformation sequence is represented as: G×X=L+ξ; where G represents the coefficient matrix; X represents the absolute deformation rate and topographic residual at the monitoring point; L represents the observed value; and ξ represents the residual value.

[0064] Step 104: Determine whether the current monitoring point is a danger point based on the deformation rate; obtain the total number of monitoring points and danger points across multiple subway lines, and calculate the surface deformation danger value. Classify the monitoring points based on height to obtain ground settlement information and building deformation information respectively.

[0065] More specifically, the method for determining a danger point is as follows: the deformation rate of the current monitoring point is compared with a set threshold. If it exceeds the set threshold, it is determined to be a danger point; otherwise, it remains a monitoring point. Preferably, the set threshold is 10 mm / year.

[0066] As an embodiment of the present invention, the method for calculating the surface deformation hazard value R is as follows:

[0067]

[0068] Among them, Num def N represents the total number of hazardous points across multiple subway lines; all This indicates the total number of monitoring points across multiple subway lines.

[0069] It should be noted that the larger the surface deformation hazard value R, the greater the potential risk of that section of the subway line.

[0070] Step 105: Based on the surface deformation hazard value, ground subsidence information and building deformation information, realize the deformation monitoring of the surface along the subway line.

[0071] It should be noted that, since subway lines are located in complex urban environments, the presence or absence of buildings on the ground will have different effects on surface deformation. Therefore, it is necessary to classify the monitoring points by height to obtain ground settlement information and building deformation information respectively.

[0072] As one embodiment of this invention, based on ground subsidence information and building deformation information, monitoring points are divided into first monitoring points corresponding to ground subsidence information and second monitoring points corresponding to building deformation information. A first preset threshold corresponding to ground subsidence information and a second preset threshold corresponding to building deformation information are also set. The determination of hazard points includes comparing the deformation rate of the first monitoring point with the first preset threshold and comparing the deformation rate of the second monitoring point with the second preset threshold. This combines ground subsidence and building deformation with surface deformation hazard values, allowing for targeted analysis of the causes of deformation and achieving large-scale hazard monitoring of urban subway networks.

[0073] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0074] It should be understood that the embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0075] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0076] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of embodiments of this disclosure upon considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

[0077] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0078] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for monitoring surface deformation along subway lines based on PS-InSAR, characterized in that, The method includes: Multiple SAR images from monitoring points along the subway line are collected. Each SAR image is preprocessed and stitched together to generate multiple sets of full-view SLC images. Each period includes one full-view SLC image, thereby obtaining multiple sets of full-view SLC images. Multiple sets of whole-scene SLC images are registered and interferometrically processed to obtain a first interferometric set. The first interferometric set includes: deformation phase, terrain phase, flat terrain phase, and atmospheric phase. The registration and interferometric processing includes: selecting a first image and multiple second images from the multiple sets of whole-scene SLC images; registering each second image with the first image to obtain multiple corresponding third images; and interferometrically processing each third image with each pixel in the first image to obtain the first interferometric set. The selection is as follows: sorting the multiple sets of whole-scene SLC images based on pixel size, marking the whole-scene SLC image with the highest pixel count as the first image, and marking the remaining whole-scene SLC images as second images. A second interferometric set is obtained based on the first interferometric set; the second interferometric set includes: deformation phase and atmospheric phase; Based on the second interferogram set, coherent points are selected, a deformation model is established, and the deformation rate, height, and deformation sequence of each monitoring point are calculated. Specifically, this includes: constructing a coherent point network, estimating arc parameters, removing atmospheric phases, and restoring deformation from the second interferogram set to obtain the deformation rate, height, and deformation sequence of each monitoring point. Determine whether the current monitoring point is a danger point based on the deformation rate; obtain the total number of monitoring points between multiple subway lines. and the total number of danger points The surface deformation hazard value was calculated. ; Based on the height, the monitoring points are classified to obtain a first monitoring point corresponding to ground settlement information and a second monitoring point corresponding to building deformation information. A first set threshold corresponding to ground settlement information and a second set threshold corresponding to building deformation information are set; the determination of the danger point includes: comparing the deformation rate of the first monitoring point with the first set threshold, comparing the deformation rate of the second monitoring point with the second set threshold, and if the set threshold is exceeded, it is determined to be a danger point; Based on surface deformation hazard values, ground subsidence information, and building deformation information, the ground subsidence information and building deformation information are combined with surface deformation hazard values ​​to analyze the causes of deformation and achieve deformation monitoring of the ground surface along the subway line.

2. The method for monitoring surface deformation along a subway line based on PS-InSAR as described in claim 1, characterized in that, The preprocessing includes: range and azimuth spectrum estimation of the SAR image, range compression, azimuth pre-filtering, azimuth autofocus and compression, and multi-view processing.

3. The method for monitoring surface deformation along a subway line based on PS-InSAR as described in claim 1, characterized in that, The SAR image is in Raw format.

4. The method for monitoring surface deformation along a subway line based on PS-InSAR as described in claim 1, characterized in that, The coherence points are selected using the amplitude deviation index.

5. A method for monitoring surface deformation along a subway line based on PS-InSAR as described in claim 1, characterized in that, The method for determining the danger point is as follows: compare the deformation rate of the current monitoring point with a set threshold. If it exceeds the set threshold, it is determined to be a danger point; otherwise, it is still a monitoring point.

6. The method for monitoring surface deformation along a subway line based on PS-InSAR as described in claim 5, characterized in that, The set threshold is 10 mm / year.

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