Optimizing Zero-Slice Feature of Ambiguity Function for Radar Emitter Identification
Radar emitter identification has attracted increasing interests in the last decade. The class-dependent method in 5 to optimize Time-Frequency kernel of ambiguity function (AF) needs to rank kernel points in the whole AF plane and is sensitive to sampling data length.In this paper,an ambiguity function zero-slice based feature optimization algorithm is proposed for radar emitter recognition.It extracts the specific feature of radar emitters efficiently and avoids out of memory problem as in large whole-plane optimization.Further,a Direct Discriminant Ratio (DDR) criterion is employed to rank the kernel points along the zero-slice of AF function. The resulting scheme not only preserves the most discriminant features of individual emitters,but also improves the recognition rate greatly. The experiments on both simulation radar data from U.S.Naval Research Laboratory and real radar emitter data demonstrate the feasibility and effectiveness of the proposed method.
radar emitter identification feature optimization intra-pulse fine features ambiguity function zero-slice
Lei Wang Hongbing Ji
School of Electronic Engineering,Xidian University,Xian 710071,China
国际会议
2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar(第二届亚太合成孔径雷达会议)
西安
英文
278-281
2009-10-26（万方平台首次上网日期，不代表论文的发表时间）