Phase unwrapping method based on factor graph
By modeling the phase unwrapping problem as a factor graph optimization problem and performing nonlinear least squares optimization, the problems of insufficient unwrapping accuracy and noise sensitivity in the existing technology are solved, and a more efficient phase unwrapping effect is achieved.
CN121880689APending Publication Date: 2026-04-17GUANGXI UNIVERSITY OF TECHNOLOGY
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Patent Information
- Application Number
- CN202511924527.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-19
- Publication Date
- 2026-04-17
AI Technical Summary
Technical Problem
Existing phase unwrapping methods suffer from insufficient unwrapping accuracy and noise sensitivity in high-precision InSAR measurements, especially under low signal-to-noise ratio conditions where error propagation is prone to occur.
Method used
The phase unwrapping problem is modeled as a factor graph optimization problem. By constructing a factor graph model and using maximum a posteriori estimation for nonlinear least squares optimization, the phase unwrapping process is optimized by combining observation factors and process factors.
Benefits of technology
It improves the continuity and consistency of unwrapping results, and enhances the unwrapping accuracy and stability under different fringe patterns and signal-to-noise ratio conditions.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention aims to provide a phase unwrapping method based on a factor graph, which comprises the following steps of: A, cutting an interferogram into a plurality of sub-interferograms with the same size by adopting a coincidence cutting mode, and reserving a plurality of rows or columns of overlapped pixels between adjacent sub-interferograms during cutting; b, constructing a phase unwrapping system equation for each sub-interferogram, then constructing a corresponding phase unwrapping factor graph model formula, and finally converting a factor graph optimization problem into a nonlinear least square optimization problem; C, carrying out iterative solution on the nonlinear least square optimization problem by adopting a Lescenberg-Marquardt method to obtain a nonlinear least square optimization problem; obtaining an unwrapping phase result of each sub-interferogram; and D, combining the unwrapping results of the sub-interferograms by using an unwrapping phase consistency criterion of adjacent regions of the interferograms to obtain an unwrapping phase of the whole interferogram. According to the phase unwrapping method, the consistency and the stability of a phase unwrapping result are improved.
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