A full non-parametric approach for SAR Coherent Change Detection

Synthetic Aperture Radar (SAR) is widely used in heterogeneous fields with aims strictly dependent on the objectives of the application. One of the most common is the exploitation of the Interferometric-SAR (InSAR) to measure millimeter movements on the Earth's surface, aiming to monitor failures or measure infrastructures' health state. In this context, developing algorithms to detect temporal and spatial changes in the radar targets becomes very important. This paper focuses on the temporal change detection framework, proposing a non-parametric Coherent Change Detection (CCD) algorithm called Permutational Change Detection (PCD). The PCD estimates the temporal Change Points (CPs) of a radar target recognizing blocks structure in the coherence matrix without making any assumptions. The performance analysis on simulated data is accomplished, considering a realistic scenario where the geometrical and temporal decorrelation are properly modeled. Finally, the PCD is compared with a parametric CCD algorithm based on the Generalized Likelihood Ratio Test (GLRT).