High-precision insar phase gradient rate calculation method, device and medium

By mapping the wrapped phase value to a complex exponential signal and using the Riesz-Gauss transfer function family for gradient extraction and noise attenuation in the frequency domain, combined with time-dimensional stacked averaging, the problems of unwrapping error and noise amplification in InSAR phase gradient rate calculation are solved, achieving high-precision deformation monitoring.

CN122307551APending Publication Date: 2026-06-30NORTHEASTERN UNIV CHINA
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NORTHEASTERN UNIV CHINA
Filing Date
2026-06-02
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing InSAR phase gradient rate calculation methods are prone to unwrapping errors in low coherence regions, resulting in insufficient deformation monitoring accuracy. Furthermore, existing gradient operators cannot be continuously adjusted according to noise levels, leading to insufficient signal-to-noise ratio and affecting the deformation boundary detection capability.

Method used

By mapping the entangled phase values ​​to complex exponential signals and extracting the real and imaginary parts, a pre-constructed family of Riesz-Gauss transfer functions is used to achieve multi-directional gradient extraction and high-frequency noise attenuation in the frequency domain. Combined with time-dimensional stacked averaging, unwinding errors are avoided and the stability of gradient calculation is improved.

Benefits of technology

It achieves high-precision phase gradient rate calculation without phase unwrapping, improves the robustness and accuracy of monitoring large-gradient deformation areas on the Earth's surface, and reduces the impact of random noise and local outliers.

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Abstract

This disclosure relates to the field of surface large-gradient deformation monitoring technology, and provides a high-precision InSAR phase gradient rate calculation method, device, and medium, including: acquiring SAR datasets and DEM data of the area to be monitored and generating differential interferograms; mapping the wrapped phase values ​​corresponding to each pixel in each differential interferogram to complex exponential signals, and determining the real and imaginary data matrices of each differential interferogram based on the real and imaginary data of each wrapped phase value extracted therefrom; determining the spatial domain directional gradient fields in multiple directions of each map based on the real and imaginary data matrices corresponding to each differential interferogram and the Riesz-Gauss transfer function family; and performing stacked averaging processing on the spatial domain directional gradient fields of all differential interferograms in the same direction to determine the phase gradient rate map of the area to be monitored. This disclosure enhances the robustness of phase gradient rate calculation in surface large-gradient deformation areas and improves the accuracy of surface large-gradient deformation monitoring.
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