Quad Polarimetry SAR Target Recognition based on Parametric Statistics and Multidimensional Analysis

Diverse parameters decomposed from quad polarimetric SAR could become the important basis in target recognition, classification and other applications. During the target recognition, due to the sidedness of single parameter or two parameters decomposed by same algorithm, obvious differences exist among the results extracted by different parameters. In this paper, a parametric statistics and multidimensional analysis algorithm will be applied in target recognition from quad polarimetric SAR image. The proposed algorithm looked the backscattering characters of land cover targets as the basis of analysis. Through parametric statistics, the dominant scattering mechanisms of every decomposing algorithm would be picked out such as volume scattering and sphere scattering of paddy. They become the data of multi dimensional analysis. In the multi-dimensional analysis, the target's location of parametric space will be the basis of target recognition. The simulation results proved that the proposed algorithm achieved better accuracy of ground features extractions. The application on land cover and land use by the proposed algorithm improved the monitoring capability of quad polarimetric SAR.