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 the identification and separation of target scattering mechanisms. Physical scattering behaviors can be characterized by polarimetric parameters from the second-order statistical observables. The average copolarization phase difference, amplitude ratio, and target coherence are important fundamental parameters for identifying scattering mechanisms. However, the individual usages of these parameters could not describe both the scattering mechanisms and the depolarization. In this paper, a new approach is proposed for scattering characterization by exploring the information contained in these three parameters. First, by assuming reflection symmetry, a new parameter is proposed for the first time to measure the scattering randomness. Then, in combination with the scattering ratio (defined by the ratio of T22 + T33 to T11), a classification plane is proposed to classify target scattering mechanisms. A validation test for this new approach is performed with three RADARSAT-2 polarimetric data 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 robust for analyzing multitemporal polarimetric SAR data.