InSAR coherence magnitude estimation based on data stack

In this paper, we present a novel approach for accurate coherence estimation, based on InSAR data stack. The main advantage of the proposed method is to meet the assumptions that the complex signals are local stationary, and meanwhile take into account the computational efficiency. Therefore, it is possible to obtain a very accurate coherence estimate without loss of resolution. Concretely, two-step is applied to adaptive algorithm: (1) nonparametric hypothesis test is firstly employed to cluster pixels with same statistical distributions; (2) the modified version of maximum likelihood fringe rate estimate is then used to eliminate the non-stationarity of complex signals. The accuracy of such estimation is improved by Cramer-Rao bounds. Experimental results with Envisat ASAR datasets over Los Angeles areas show that the new method performs well under different situations.