An Airport Deformation Monitoring Method Based on Multi-Feature Scatterers of Amplitude Intensity

Abstract

The present invention discloses an airport deformation monitoring method for multi-feature scatterers based on amplitude intensity, including: generating an interferometric pair from SAR image data whose spatio-temporal baselines all meet the threshold in the SAR image data, estimating the coherence of the generated interferometric pair, determining the coherence threshold, and dividing out the low-coherence regions. Artificial corner reflectors are arranged in the low-coherence regions, the backscattering coefficient amplitude deviation coefficient and the amplitude mean coefficient are obtained, the amplitude deviation coefficient is used as the primary selection threshold for scatterers, a relatively large number of primary surface scatterers are obtained, and the deformation information of the primary surface scatterers is obtained. The amplitude mean coefficient is used as the selection threshold for correction points, a certain number of correction points are obtained, the obtained correction points are networked with the primary surface scatterers with similar coherence in the vicinity, and indirect adjustment is performed between the correction points and the primary surface scatterers to obtain high-precision deformation information for the region. This method can overcome the influence of regional decoherence on the accuracy, and has high efficiency and extremely low cost.

Description

Technical Field

[0001] The present invention relates to the technical field of deformation monitoring, and more specifically to an airport deformation monitoring method based on multi-feature scatterers of amplitude intensity. Background Art

[0002] With the implementation and promotion of the "National Comprehensive Three-dimensional Transportation Network Planning Outline", a large number of mountainous regional airports have been built in mountainous areas of our country. Due to the complex geological conditions in mountainous areas, airport deformation monitoring and stability analysis have gradually become hot issues.

[0003] Currently, for surface deformation monitoring methods in mountainous airport areas, there are GNSS measurement, leveling measurement, and layered calibration technology. The above technical solutions can all obtain discrete high-precision point deformation amounts. However, due to their high labor and equipment costs, being restricted by terrain factors and it is not easy to obtain the large-area overall deformation distribution in expansive soil areas, there is a need for a high-precision, large-scale, long-term deformation monitoring technology. Summary of the Invention

[0004] An embodiment of the present invention provides an airport deformation monitoring method based on multi-feature scatterers of amplitude intensity, including:

[0005] Obtaining SAR image data with spatio-temporal baselines all meeting the threshold in SAR image data to generate an interference pair;

[0006] Performing coherence estimation on the generated interference pair to determine the coherence threshold;

[0007] Dividing the low-coherence region according to the coherence threshold;

[0008] Deploying artificial corner reflectors in the low-coherence region;

[0009] Obtaining the backscattering coefficient amplitude deviation coefficient and amplitude mean coefficient of the artificial corner reflector;

[0010] Taking the amplitude deviation coefficient as the scatterer primary selection threshold, obtaining a relatively large number of primary surface scatterers, and obtaining the deformation information of the primary surface scatterers based on PS-InSAR technology;

[0011] Taking the amplitude mean coefficient as the selection threshold for correction points, obtaining a certain number of correction points;

[0012] Networking the obtained correction points with the primary surface scatterers with similar coherence in the vicinity, and performing indirect adjustment of the correction points and the primary surface scatterers based on CR-InSAR technology to obtain high-precision regional deformation information.

[0013] Furthermore, it also includes preprocessing of SAR image data:

[0014] Selecting a reference image in the SAR image data;

[0015] Remove the Doppler effect from the reference image based on precise orbit data;

[0016] Register and crop the reference image using the digital elevation model (DEM), and output the preprocessing results.

[0017] Furthermore, estimate the coherence of the generated interferometric pairs, including:

[0018] Calculate the offset between interferometric pairs of the preprocessed data;

[0019] Generate a precise coding table using the offset between interferometric pairs;

[0020] Recode the DEM and SAR images using the precise coding table;

[0021] Set the time baseline and spatial baseline thresholds, and perform differential interferometry and calculate the coherence of the interferometric pairs by combining the recoded DEM and intensity information.

[0022] Furthermore, obtain the deformation information of the initially selected surface scatterers based on the PS-InSAR technique, including:

[0023] Select the master image and perform initial selection of surface scatter points according to the initially selected threshold determined by the amplitude deviation;

[0024] Unwrap the phase of the initially selected surface scatter points using the minimum cost flow algorithm;

[0025] Perform spatio-temporal filtering on the unwrapped phase to remove the atmospheric phase;

[0026] Calculate the linear and non-linear deformations of the initially selected surface scatterers respectively according to the spatio-temporal filtering results, and obtain the time series deformation amounts of the initially selected surface scatterers.

[0027] Furthermore, perform indirect adjustment between the correction points and the initially selected surface scatterers based on the CR-InSAR technique, including:

[0028] Identify obvious CR points on the SAR image according to the row and column numbers of the CR points;

[0029] Set a threshold based on the average amplitude of the CR points to select the adjustment reference points;

[0030] Select high-stability scatter points according to the adjustment reference points;

[0031] Perform phase difference on the high-stability scatter points;

[0032] Unwrap the differential phase using the Lambda algorithm;

[0033] Extract the deformation phase from the unwrapped phase;

[0034] Indirect adjustment is performed on the scatterers within the window adjacent to the reference point;

[0035] Obtain the deformation information of the study area.

[0036] The embodiment of the present invention provides an airport deformation monitoring method based on multi-feature scatterers of amplitude intensity. Compared with the prior art, its beneficial effects are as follows:

[0037] 1. The multi-source remote sensing data used in the present invention is obtained simply and quickly, overcomes the influence of regional decorrelation on accuracy and has high efficiency, and the human and material costs are extremely low.

[0038] 2. The present invention provides a high-precision monitoring means for mountain airports at the centimeter level or even millimeter level. According to the regional coherence and amplitude information, regional and hierarchical observations can be carried out, which can significantly improve the monitoring accuracy of areas with poor observation conditions, realize the continuous monitoring of large ranges and long periods in the mountain airport area, without missing deformation information, and facilitate the analysis and interpretation of the overall deformation mechanism. Brief Description of the Drawings

[0039] Figure 1 It is the monitoring technical flow chart provided by the embodiment of the present invention;

[0040] Figure 2 It is the coherence coefficient distribution diagram provided by the embodiment of the present invention;

[0041] Figure 3 It is the corner reflector identification diagram provided by the embodiment of the present invention;

[0042] Figure 4 It is the corrected deformation rate diagram of a certain mountain airport provided by the embodiment of the present invention;

[0043] Figure 5 It is the feature point accuracy verification diagram provided by the embodiment of the present invention. Detailed Embodiment

[0044] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the 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 of 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.

[0045] See Figures 1 to 5 , the embodiment of the present invention provides an airport deformation monitoring method based on multi-feature scatterers of amplitude intensity, and the method includes:

[0046] STP1: Generate an interference pair from the SAR image data in which the spatio-temporal baselines in the SAR image data all meet the threshold;

[0047] STP2: Estimate the coherence of the generated interference pairs and determine the coherence threshold;

[0048] STP3: Divide the low-coherence regions according to the coherence threshold;

[0049] STP4: Deploy artificial corner reflectors in the low-coherence regions;

[0050] STP5: Obtain the amplitude deviation coefficient and the amplitude mean coefficient of the backscattering coefficient of the artificial corner reflectors;

[0051] STP6: Use the amplitude deviation coefficient as the primary selection threshold for scatterers, obtain a relatively large number of primary surface scatterers, and obtain the deformation information of the primary surface scatterers based on the PS-InSAR technology;

[0052] STP7: Use the amplitude mean coefficient as the selection threshold for correction points to obtain a certain number of correction points;

[0053] STP8: Network the obtained correction points with the primary surface scatterers with similar coherence in the vicinity, and perform indirect adjustment of the correction points and the primary surface scatterers based on the CR-InSAR technology to obtain high-precision deformation information of the region.

[0054] It also includes preprocessing of SAR image data:

[0055] Select a reference image from the SAR image data;

[0056] Remove the Doppler effect from the reference image based on precise orbit data;

[0057] Register and crop the reference image using the digital elevation model DEM, and output the preprocessing result.

[0058] Specifically, in STP2, estimating the coherence of the generated interference pairs includes:

[0059] Calculate the offset between the interference pairs of the preprocessed data;

[0060] Generate a precise coding table using the offset between the interference pairs;

[0061] Recode the DEM and the SAR image using the precise coding table;

[0062] Set the time baseline and the space baseline thresholds, and perform differential interferometry and calculate the coherence of the interference pairs by combining the recoded DEM and the intensity information.

[0063] Specifically, in STP6, obtaining the deformation information of the primary surface scatterers based on the PS-InSAR technology includes:

[0064] Select the main image and conduct a preliminary selection of surface scatter points according to the preliminary selection threshold determined by the amplitude deviation;

[0065] Perform phase unwrapping on the preliminarily selected surface scatter points using the minimum cost flow algorithm;

[0066] Perform spatio-temporal filtering on the unwrapped phase to remove the atmospheric phase;

[0067] Calculate the linear deformation and non-linear deformation of the preliminarily selected surface scatterers respectively according to the spatio-temporal filtering results, and obtain the time series deformation amounts of the preliminarily selected surface scatterers.

[0068] Specifically, in STP8, indirect adjustment of correction points and preliminarily selected surface scatterers is carried out based on the CR-InSAR technology, including:

[0069] Identify obvious CR points on the SAR image according to the row and column numbers of the CR points;

[0070] Set a threshold based on the average amplitude of the CR points to select the adjustment reference points;

[0071] Screen out high-stability scatter points according to the adjustment reference points;

[0072] Perform phase difference on the high-stability scatter points;

[0073] Unwrap the differential phase using the Lambda algorithm;

[0074] Extract the deformation phase from the unwrapped phase;

[0075] Perform indirect adjustment on the scatter points within the adjacent window of the reference point;

[0076] Obtain the deformation information of the study area.

[0077] Example:

[0078] Figure 1 is the technical flow chart for the solution of this technical solution

[0079] Figure 2 is the coherence coefficient distribution map of this monitoring example (mountain airport). SAR (Synthetic Aperture Radar) image data is used. Based on InSAR (Interferometric Synthetic Aperture Radar technology), differential interferogram pairs of the study area are generated, and the coherence coefficients of the interferogram pairs are weighted and averaged to obtain the spatial distribution information of the average coherence coefficient of the monitoring area. A coherence coefficient threshold is set to divide the monitoring area into high and low coherence regions, thereby providing judgment materials for the layout of artificial corner reflectors.

[0080] Figure 3This is the identification diagram of the artificial corner reflector for this monitoring example. SAR (Synthetic Aperture Radar) image data is used. According to the precise coordinates collected by artificial layout, the position of the artificial corner reflector is successfully identified, and the amplitude intensity information of the pixels adjacent to the corner reflector is obtained. The average amplitude threshold is calculated, and the ground scattering points with stability similar to that of the artificial corner reflector in the study area are obtained as the adjustment reference points.

[0081] Figure 4 This is the post-adjustment surface deformation rate distribution map of the example area (mountain airport) solved by this technical solution. Figure 4 It can clearly show the distribution of surface deformation in the example area. The maximum deformation in the area appears in the filled slope areas on both sides of the airport runway, and the maximum deformation rate reaches -45 mm·year-1. Three deformation areas, namely Area I, Area II, and Area III, are successfully identified. Among them, Area I and Area II are in Figure 2 the severely decoherent areas in the coherence coefficient map, and it is difficult to obtain reliable deformation information. However, Figure 4 the deformation areas are successfully identified, which proves that this technical solution overcomes the limitation of decoherence caused by poor observation conditions in InSAR technology to a certain extent.

[0082] Figure 5 This is the accuracy verification diagram of the post-adjustment time-series deformation result and the leveling measurement value in the area with poor observation conditions in the example area (mountain airport) solved by this technical solution. From Figure 5 it can be seen that the two monitoring methods have good consistency, showing an obvious strong linear correlation. R2 = 0.92, MSE = 9.92, which fully demonstrates the reliability and stability of this monitoring technology.

[0083] The above-disclosed are only several specific embodiments of the present invention. Those skilled in the art can make various changes and modifications to the embodiments of the present invention without departing from the spirit and scope of the present invention. However, the embodiments of the present invention are not limited thereto, and any changes that can be thought of by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. An airport deformation monitoring method for multi-feature scatterers based on amplitude intensity, characterized in that Including: Obtain SAR image data that meet the threshold of spatio-temporal baseline in the SAR image data to generate an interferometric pair; Perform coherence estimation on the generated interferometric pair to determine the coherence threshold; Divide the high-coherence region and the low-coherence region according to the coherence threshold; Deploy artificial corner reflectors in the low-coherence region and select a differential master image in the high-coherence region; Obtain the backscattering coefficient amplitude deviation coefficient and the amplitude mean coefficient of the artificial corner reflector; Use the amplitude deviation coefficient as the primary selection threshold for scatterers, obtain a set number of primary surface scatterers, and obtain the deformation information of the primary surface scatterers based on the PS-InSAR technology; The obtaining of the deformation information of the primary surface scatterers based on the PS-InSAR technology includes: selecting a master image, performing primary selection of surface scatter points according to the primary selection threshold determined by the amplitude deviation; performing phase unwrapping on the primary selected surface scatter points using the minimum cost flow algorithm; performing spatio-temporal filtering on the unwrapped phase to remove the atmospheric phase; calculating the linear deformation and non-linear deformation of the primary surface scatterers respectively according to the spatio-temporal filtering results to obtain the time series deformation amount of the primary surface scatterers; Use the amplitude mean coefficient as the selection threshold for correction points to obtain a set number of correction points; Network the obtained correction points with the primary surface scatterers with similar coherence in the vicinity, and perform indirect adjustment of the correction points and the primary surface scatterers based on the CR-InSAR technology to obtain the high-precision deformation time series and deformation rate of the region.

2. The airport deformation monitoring method for a multi-feature scatterer based on amplitude intensity according to claim 1, characterized in that, It also includes preprocessing of the SAR image data: Select a reference image from the SAR image data; Remove the Doppler effect from the reference image based on precise orbit data; Register and crop the reference image using the digital elevation model DEM, and output the preprocessing result.

3. The airport deformation monitoring method for a multi-feature scatterer based on amplitude intensity according to claim 2, wherein The coherence estimation of the generated interferometric pair includes: Calculate the offset between the interferometric pairs of the preprocessed data; Generate a precise coding table using the offset between the interferometric pairs; Recode the DEM and the SAR image using the precise coding table; Set the time baseline and space baseline thresholds, and perform differential interferometry and calculate the coherence of the interferometric pair by combining the recoded DEM and the intensity information.

4. The airport deformation monitoring method for a multi-feature scatterer based on amplitude intensity according to claim 1, characterized in that The indirect adjustment of the correction points and the primary surface scatterers based on the CR-InSAR technology includes: Identify obvious CR points on the SAR image according to the row and column numbers of the CR points; Reasonably set the threshold based on the amplitude mean of the CR points to select the adjustment reference points; Screen out high-stability scatter points according to the adjustment reference points; Perform phase difference on the high-stability scatter points; Unwrap the differential phase using the Lambda algorithm; Extract the deformation phase from the unwrapped phase; Perform indirect adjustment on the scatter points within the adjacent window of the reference point; Obtain the deformation information of the study area.

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