Ground-based radar adaptive threshold permanent scatterer identification method and device and storage medium

Abstract

The invention relates to a ground-based radar self-adaptive threshold permanent scatterer recognition method and device and a storage medium. The method comprises the following steps: performing grouping operation on acquired time sequence SAR (Synthetic Aperture Radar) images; obtaining a candidate permanent scatterer point set of each group of SAR images by using an amplitude threshold method; generating a coherence coefficient sequence based on the coherence coefficient of each pixel in the candidate permanent scatterer point set so as to obtain a high-coherence permanent scatterer class through a clustering algorithm; based on the amplitude deviation information and the phase stability information of each pixel in the high-coherence permanent scatterer class, respectively obtaining a corresponding low-amplitude deviation permanent scatterer class and a high-phase stability permanent scatterer class through a clustering algorithm; and identifying target permanent scatterer points based on the low-amplitude-deviation permanent scatterer class and the high-phase-stability permanent scatterer class. According to the embodiments of the invention, the stability of the number of the PS points can be greatly improved, the self-adaptive threshold PS point selection of the ground-based radar is realized, and a good foundation is laid for high-precision deformation inversion.

Description

technical field [0001] The present disclosure relates to the technical field of radar interferometry data processing, and in particular to a ground-based radar adaptive threshold permanent scatterer identification method, a ground-based radar adaptive threshold permanent scatterer identification device, and a computer-readable storage medium. Background technique [0002] The permanent scatterers (Permanent Scatterers, PS) point selection methods in the prior art often need to set a fixed threshold to achieve, which easily leads to misselection and missed selection of PS points. Due to the complex environment of Ground-based Interferometric Synthetic Aperture Radar (GB-InSAR) during the long-term observation process, the monitoring results are affected to a certain extent, resulting in the disappearance or new generation of PS points. If only relying on fixed thresholds to select PS points, the adaptability to different scenarios cannot be achieved, which may cause PS points...

AI Technical Summary

Problems solved by technology

[0002] In the prior art, permanent scatterers (Permanent Scatterers, PS) point selection methods often need to set a fixed threshold to achieve, which is easy to cause misselection and missed selection of PS points

Due to the complex environment of Ground-based Interferometric Synthetic Aperture Radar (GB-InSAR) during the long-term observation process, the monitoring results are affected to a certain extent, resulting in PS points disappearing or emerging.

If only relying on fixed thresholds to select PS points, the adaptability to different scenarios cannot be achieved, which may cause PS points not to be updated in time, resulting in the number of PS points screened out during the long-term observation process. The difference in quality will introduce a large deformation inversion error, which will affect the final deformation inversion result

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