Weighted Kalman Filter Phase Unwrapping Algorithm Based on the Phase Derivative Variance Map

Abstract:

The kalman filtering phase unwrapping is a state estimation problem. It can realize phase unwrapping and noise elimination at the same time, and calculate the real phase by establishing the state space model and vector observation model. In the steep terrain, the conventional kalman filtering algorithm unwrapping results are often not accurate, easy to cause the error transfer. Aiming at this problem, the weighted kalman filter phase unwrapping algorithm based on the phase derivative variance map is proposed. The values of the phase derivative variance maps are applied to determine the noise variance in the observation equation, then the weighted kalman filter is used to unwrap phase, this can increase the accuracy of the results. Finally, experiments are carried out in the InSAR data application under the condition of steep terrain, and with the conventional kalman filtering phase unwrapping algorithm are compared, the effectiveness of the proposed method is verified.

• Periodical: Applied Mechanics and Materials (Volumes 475-476)
• Pages: 991-995
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.475-476.991
• Online since: December 2013
• Authors: Li Fen Wang, Man Yan
• Keywords: InSAR, Phase Derivative Variance Map, Phase Unwrapping, Weighted Kalman Filter

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