Deformation rate estimation method and system

Abstract

The invention relates to a deformation rate estimation method and system, and the method comprises the steps: recognizing homogeneous pixels, and constructing a coherence matrix; performing eigenvalue decomposition and principal component analysis on the coherence matrix to obtain an optimized phase; calculating time coherence according to the interferometric phase with low noise and clear fringes; selecting a distributed scatterer according to a homogeneous pixel preset threshold value and a time coherence preset threshold value; and performing combined processing on the distributed scatterer and the permanent scatterer, and estimating the deformation rate of each measurement point. According to the embodiment of the invention, the coherence matrix is constructed according to the homogeneous pixels, so that the problem of deviation caused by the participation of heterogeneous pixels in matrix estimation can be avoided; compared with a covariance matrix, the coherence matrix can avoid the influence of back scattering power imbalance possibly existing in the image; the time coherence is calculated by adopting an interference phase with low noise and clear fringes, so that the influence of the low-quality interference phase can be avoided; and principal component analysis is performed after eigenvalue decomposition of the coherence matrix, so that the operation efficiency of phase optimization can be improved.

Description

technical field [0001] The invention relates to the technical field of surface deformation monitoring, in particular to a deformation rate estimation method and system. Background technique [0002] Surface deformation is a relatively common geological disaster. Interferometric Synthetic Aperture Radar (InSAR) is a new technology for earth observation in the 1990s. Time-series InSAR techniques, such as Permanent scatterer (PS) interferometry and Small Baseline Subset (SBAS) interferometry, are widely used in surface deformation monitoring. However, such methods focus on extracting PS with high reflectance values, which are slightly affected by temporal and geometric de-coherence, and obtain fewer points in non-building areas. Since the second-generation permanent scatterer technology SqueeSAR was proposed, scholars at home and abroad have turned their research focus to the pixels in the medium coherence area in some interference pairs. In these areas, many adjacent pixels ...

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Problems solved by technology

[0004] However, this algorithm has several deficiencies: (1) The covariance matrix is ​​calculated according to the mean value of the neighborhood pixels in the regular boxcar window, if the pixels in the window do not belong to the same feature, there is a bias in the estimation; (2 ) studies on the covariance matrix are susceptible to backscattering power imbalance between SAR images; (3) in the process of phase optimization, the temporal coherence is determined according to all possible combinations of N(N-1) / 2 The phase of interferometric pairs is calculated, N is the number of SAR images, and the influence of low-quality interferometric phase is ignored

These inadequacies are not conducive to DS extraction and phase optimization, and are not conducive to surface deformation estimation

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