Target detection based on eigen-decomposition using PolInSAR data

In this paper, an eigenvalue decomposition method of the simplified polarimetric interferometric coherency matrix (SPICM) is proposed for polarimetric SAR interferometry (PolInSAR) data analysis. Firstly, the definition of the SPICM is given. Then, the characteristics of this matrix are analyzed and connected with the polarimetric scattering mechanism of targets and clutter objects. Further more the eigenvalue decomposition method is described in detail. The polarimetric scattering vectors can be converted to optimal states, in which the optimal coherence between the signals in same polarimetric states of two antennas can be obtained. Finally, the method is verified with ESAR data. The results show that the proposed method is promising in classification or recognition of man-made targets such as buildings.