InSAR Phase Unwrapping Based on Square-Root Cubature Kalman Filter
Xiaomei Luo, Hongtao Li, Zhi‐Long Dong, Shengqi Zhu
Abstract
In this article, we propose a novel phase unwrapping method termed the square-root cubature Kalman filter phase unwrapping (SCKFPU) method. Specifically, as the system model of the interferometric synthetic aperture (InSAR) phase unwrapping can be formulated as the discrete Markovian jump system for tracking a maneuvering target, a phase unwrapping method is proposed by combining the SCKF algorithm with a phase gradient estimator. Moreover, we design a phase quality estimate function, and present an optimal path-following strategy. The strategy ensures that the SCKFPU method simultaneously performs noise suppression and unwraps InSAR images along the pixels with high-reliance to the pixels with low-reliance. Simulation results based on synthetic data, true InSAR data, and measured (real) InSAR data show that the proposed InSAR phase unwrapping method can achieve better performance compared with other existing phase unwrapping methods.