Radar target recognition using SVMs with a wrapper feature selection driven by Immune Clonal Algorithm

摘要

A wrapper feature selection method based on Immune Clonal Algorithm for SVM is presented and applied to 1 -D images recognition of radar targets in this paper. In the proposed method, the cross-validation is used for feature evaluation in wrapper feature selection step for SVMs. And Immune Clonal Algorithm, which is characterized by rapid convergence to global optimal solution, is applied to find the optimal feature subset. Experimental results on 1-D images of 3 airplanes obtained in a microwave anechoic chamber show the effectiveness of the proposed method.