Ship detection using weighted SVM and M-CHI decomposition in compact polarimetric SAR imagery

This paper proposes a ship detection method based on weighted support vector machines (SVM) and m-χ decomposition in compact polarimetric (CP) synthetic aperture radar (SAR) imagery. Firstly, the proposed method constructs the weighted feature vectors by extracting CP parameters. Each feature will be weighted by the ReliefF method. Then, ship targets in CP SAR imagery are detected by the weighted SVM classifier. Finally, false alarms are removed by scattering mechanism strength differences corresponding to three components of m-χ decomposition. NASA/JPL AIRSAR airborne quad-polarimetric (QP) data are used to simulate the CP data in the circular transmitlinear receive (CTLR) mode. Experimental results show that the method performs well in detecting ship targets, and can reject azimuth ambiguities.