Interferometric Phase Stack Data Filter Method via Bayesian CP Factorization

Rui Wang, Yanan You, Wenli Zhou

Abstract: The filter based on tensor decomposition is an effective method to remove the noise of the interferometric phase stack data. The key is to choose the definition of tensor rank and an appropriate tensor decomposition model. The Bayesian CP Factorization (BCPF) -InSAR framework proposed in this paper definites the rank of InSAR tensor by CP rank and decomposes InSAR tensor into low rank tensor, noise tensor and outlier tensor. Compared with several widespread filters, BCPF-InSAR is proved as an effective InSAR tensor filtering method on the simulation data and real data.