Regularization solution of Small Baseline Subset Deformation Model Inversion

doi:10.11947/j.AGCS.2016.20150143

Abstract

Abstract: For the coefficient matrix of the normal equation is ill-conditioned during inverting deformation model of small baseline subset (SBAS) InSAR technique, a regularization robust method is proposed. Based on Tikhonov regularization theory, this method converts the problem of how to solve the deformation rate into minimization problem. According to L-curve method to choose regularization parameter, considering the relationship between the individual components of least-squares residuals to choose regularization matrix, thus it achieves robust solution of SBAS deformation model inversion. We adopt respectively least-squares estimation, ridge estimation and Tikhonov regularization method to deal with 29 ENVISAT ASAR dataset relevant to the Beijing area, achieving the subsidence rate map of the study area. Through comparative analysis among the mean square error (MSE) of 21 points on behalf of the different subsidence, temporal coherence values and MSE maps of the entire study area, we confirm that Tikhonov regularization robust method in inverting SBAS deformation model can obtain more reliable results of deformation monitoring.

Key words: small baseline subset, condition number, Tikhonov regularization, ridge estimation, mean squared error

CLC Number:

P226

JIANG Zhaoying, LIU Guolin, TAO Qiuxiang. Regularization solution of Small Baseline Subset Deformation Model Inversion[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(5): 566-573.

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