Unknown and Arbitrary Sparse Signal Detection Against Background Noise

摘要：

The problem of detecting unknown and arbitrary sparse signals against background noise is considered. Under a fixed hypothesis-testing problem model, a scheme referred to as Likelihood Ratio Test with Sparse Estimate (LRT-SE) is proposed. The relation between the quality of the estimate and the detection performance is quantized through the Kullback-Leibler distance, which shows the performance of LRT-SE is only a function of the angle between the sparse signal and its estimate, thus accurate estimation of signal energy is not necessary. An algorithm of LRT-SE is further proposed. Sufficient conditions on the sparsity level and the angle between the sparse signal and its estimate are given such that Chernoff-consistent detection is achievable. Simulation results show LRT-SE gives close performance to that of likelihood ratio test without knowing the underlying sparse signal.

关键词： Sparse signal detection Likelihood ratio test Sparse estimation

作者: Chuan Lei Jun Zhang Qiang Gao

作者单位: School of Electrical and Information Engineering, Beihang University, Beijing 100191, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 46-49

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）