Novel Model-Based Method for Identification of Scattering Mechanisms in Polarimetric SAR Data


One basic issue of importance in polarimetric synthetic aperture radar (SAR) imagery is that the identification and separation of target scattering mechanisms. Physical scattering behaviors can be characterised by polarimetric parameters from the second-order statistical observables. The typical copolarization phase distinction, amplitude ratio, and target coherence are vital basic parameters for identifying scattering mechanisms. But, the individual usages of these parameters might not describe each the scattering mechanisms and the depolarization. During this paper, a replacement approach is proposed for scattering characterization by exploring the data contained in these 3 parameters. Initial, by assuming reflection symmetry, a new parameter is proposed for the primary time to measure the scattering randomness. Then, together with the scattering ratio (defined by the ratio of to ), a classification plane is proposed to classify target scattering mechanisms. A validation check for this new approach is performed with 3 RADARSAT-two polarimetric knowledge sets acquired over two study areas: the San Francisco Bay area and Fuzhou, China. Results show that the new approach is very promising for distinguishing orientated targets (with respect to the radar azimuth direction) in urban areas from natural scatterers such as forests, and it also shows that the new method is sturdy for analyzing multitemporal polarimetric SAR data.

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