Abstract

Phase unwrapping (PU) is a key step for the synthetic aperture radar (SAR) interferometry (InSAR). Single-baseline (SB) PU and multi-baseline (MB) PU are two independently developed technologies, each of which has its own advantages and disadvantages. A two-stage programming-based MB PU method (TSPA) proposed by Yu [1] establishes a connection between the MB and SB PU methods. TSPA breaks the limitation of the phase continuity assumption by using the Chinese remainder theorem (CRT), and uses the minimum-cost flow (MCF) optimization model to obtain the PU result. TSPA can be regarded as a framework for solving MB PU problems. In this paper, we studied how to transplant the infinity-norm ( $L^{\infty}$ -norm) optimization model into TSPA framework. Under the TSPA MB PU framework, a $L^{\infty}$ -norm based MB PU method (referred to as Inf-TSPA) is proposed to solve the problem of low PU accuracy of the $L^{\infty}$ -norm SB PU method. The experimental results on the simulated and the realistic MB InSAR data sets verify that the performance of Inf-TSPA is significantly improved compared to the $L^{\infty}$ -norm SB PU method.

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