Adaptive CFAR Detection of Range-Spread Targets Based on SAR Raw Data
Conventionally, SAR Automatic Target Detection（ATD ） are often performed in SAR image domain. A novel scheme of SAR target detection in the state of non-imaging is presented. More precisely, this paper addresses adaptive detection of SAR possibly extended targets when implemented on range-compressed but azimuth-uncompressed SAR raw data, rather than the processed SAR image. The SAR target detection is established in the context of space-time adaptive processing (STAP) and the spatial-temporal steering vector of an airborne stripmap SAR is first derived by exploiting signature diversity, namely of the fact that SAR can change the transmitted signal as the azimuth varies. The generalized adaptive subspace detector (GASD) is employed to detect range-spread target from SAR raw data. Performance analysis of the proposed scheme is carried out via Monte Carlo simulation which shows the validity of the new scheme in possible realistic scenarios.
SAR Automatic Target Detection CFAR raw data
ZHANG Yanfei GUAN Jian Li Xiuyou HUANG Yong
Department of Electronic and Information Engineering,Naval Aeronautical Engineering Institute,Yantai City,264001,China
国际会议
首届亚太合成孔径雷达会议(1st Asian and Pacific Conference on Synthetic Aperture Radar Proceedings)
安徽黄山
英文
2007-11-05（万方平台首次上网日期，不代表论文的发表时间）