A Novel Mixed-Norm Multibaseline Phase-Unwrapping Algorithm Based on Linear Programming

• Published in: IEEE geoscience and remote sensing letters Vol. 12; no. 5; pp. 1086 - 1090
• Main Authors: Liu, Huitao, Xing, Mengdao, Bao, Zheng
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.05.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Cost function; Linear programming; Memory management; mixed-norm; multibaseline; Noise; Optimization; phase unwrapping (PU); Remote sensing; Synthetic aperture radar; synthetic aperture radar interferometry; Linear programming; multibaseline; phase unwrapping (PU); mixed-norm; synthetic aperture radar interferometry
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2014.2381666

The multibaseline phase unwrapping (PU) of L 1 -norm can be efficiently solved using linear programming. However, the huge memory requirement of linear programming limits its application in multibaseline PU for large-scale data. In order to reduce the required memory when linear programming is performed, a novel mixed-norm multibaseline PU algorithm is proposed in this letter, which is regarded as an approximation of the L 1 -norm method. In this method, an L∞-norm cost function is employed to substitute for that of the L 1 -norm, i.e., it takes the optimization which is aimed to minimize the maximum component of the optimization variable as the representation of the one that minimizes the absolute sum of L 1 -norm. Consequently, the cost function in the proposed method changes to be an L 1 -norm plus an L ∞ -norm. Compared with the traditional L 1 -norm method, the size of the optimization variable in the proposed method is generally reduced by about one-seventh. Therefore, it is logical that less memory is needed in the proposed algorithm. The effectiveness of the proposed algorithm is validated via a simulated and real repeat-pass interferometric-synthetic-aperture-radar data set.