Abstract
Phase unwrapping is one of the most critical steps in InSAR data processing. Filter-based phase unwrapping methods can perform phase unwrapping and noise removal simultaneously, and show a clear advantage in dealing with high noise and density fringe interferograms. Based on the precision estimation theory of nonlinear functions in Extended Kalman Filter (EKF) and Cubature Kalman Filter (CKF) algorithms, we derive and analyze in detail the estimated precision of the EKF and the CKF on nonlinear observation equations in the phase unwrapping model. Results show that both EKF and CKF algorithms have similar precision in areas with better phase quality. However, in poorer quality areas, the precision of the two shows a certain difference and there is no consistent superiority for each algorithm. Experiments using simulated and measurement data confirm the validity of our theoretical analysis.
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