文献类型：期刊文献

英文题名：New Approximate Distributions for the Generalized Likelihood Ratio Test Detection in Passive Radar

作者：Chen, Yunfei[1,2];Wu, Yue[1];Chen, Ning[1];Feng, Wei[3,4];Zhang, Jie[1,5]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]Univ Warwick, Sch Engn, Coventry CV4 7AL, W Midlands, England;[3]Peng Cheng Lab, Shenzhen 518000, Peoples R China;[4]Tsinghua Univ, Beijing Natl Res Ctr Informat Sci & Technol, Beijing 100084, Peoples R China;[5]Univ Sheffield, Dept Elect & Elect Engn, Sheffield S1 4DE, S Yorkshire, England

年份：2019

卷号：26

期号：5

起止页码：685

外文期刊名：IEEE SIGNAL PROCESSING LETTERS

收录：;EI(收录号：20191506746571);WOS:【SCI-EXPANDED(收录号:WOS:000463068400004)】；

基金：The work of Y. Wu was supported by Shanghai Sailing Program (18YF1405300). The work of N. Chen was supported by the National Natural Science Foundation of China under Grant 61771196. The work of W. Feng was supported in part by the Beijing Natural Science Foundation under Grant L172041 and in part by the National Science Foundation of China under Grants 61771286 and 61701457. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Augusto Aubry.

语种：英文

外文关键词：Approximations; generalized likelihood ratio test; target detection; passive radar

摘要：Generalized likelihood ratio test is an effective method for target detection in passive radar systems. The distribution of its decision variable in the presence of a direct path is unknown but is required for the calculation of the detection threshold and the detection probability. In this letter, several new approximations to this distribution are proposed by using moment matching. Numerical results show that the generalized extreme value approximation works consistently well for both null and alternative hypotheses with large or small signal-to-noise ratios. On the other hand, the Gaussian and logistic approximations only work well in the null hypothesis.