雷达学报Issue(4)：414-419,6.DOI:10.3724/SP.J.1300.2012.20097
基于半参数化SLC的雷达目标识别
Radar Target Recognition Based on Semiparametric Density Estimation of SLC
摘要
Abstract
In order to solve the problem of the decline of accuracy when using the nonparametric method—Stochastic Learning of the Cumulative (SLC) to estimate the density of High-Resolution Range Profile (HRRP) in radar target recognition under the condition that the samples are not enough, a radar target recognition approach based on the semiparametric density estimation of SLC is proposed in this paper. This method has the ability to make use of empirical knowledge which is known as the approximate Gamma distribution of amplitudes in each HRRP range cells, and the Gamma density estimate is then corrected by multiplying with SLC of a correction factor. Obviously, both advantages of parametric method and nonparametric method of SLC are merged in the semiparametric density estimation of SLC. Simulation results based on the HRRP dataset of five aircraft models demonstrate the effectiveness of the proposed approach.关键词
雷达目标识别/高分辨距离像(HRRP)/概率密度估计/半参数化SLCKey words
Radar target recognition/High-Resolution Range Profile (HRRP)/Density estimation/Semiparametric density estimation of SLC (Stochastic Learning of the Cumulative)分类
信息技术与安全科学引用本文复制引用
崔姗姗,周建江,朱劼昊..基于半参数化SLC的雷达目标识别[J].雷达学报,2012,(4):414-419,6.基金项目
中航工业合作创新产学研项目资助(CXY2010NH15)和江苏高校优势学科建设工程项目资助课题 （CXY2010NH15）
