Model-Free Characterization of SAR MTI Time Series

Multitemporal interferometric synthetic aperture radar (MTI) displacement time series are usually characterized by the model-dependent temporal phase coherence as a quality measure. Additional tests have to be performed recognize other “interesting” but nonmodeled trends, and several automated approaches this task been proposed date. We introduce here fuzzy entropy ( $F_{E}$ ), measure introduced in medical data analysis, viable parameter characterize MTI series. Being of disorder series, exhibits homogeneously low values for large class models, such seasonal, parabolic, or piecewise linear signals, while increasing more chaotic dominated noise. It appears therefore suited discriminative isolate meaningful within sets, without specifying predefined model. The calculation has computational cost can thus easily prescreening filter. In letter, results over simulated some examples on real set shown with interesting performances which hint possible large-scale implementations.