ESPRIT Matching Pursuit Algorithm for DOA Estimation With Single Snapshot
For a uniform linear array, classical DOA estimation methods, such as ESPRIT etc., with a space smoothing preprocessing, can be applied to the case of single snapshot. Due to the spatial sparsity, this DOA estimation problem can be translated into a sparse signal recovery problem. Then we can use some sparse recovery methods to resolve DOAs. As a highly efficient method among those, the orthogonal matching pursuit (OMP) algorithm is considered at first. It has been observed that OMP can offer DOA estimates with smaller mean-square errors than ESPRIT at low SNRs; however, an opposite conclusion will be drawn at high SNRs. Combining the advantages of the both methods, we present a novel ESPRIT matching pursuit (EMP) algorithm, which takes a full utilization of ESPRIT and a maximum correlation method in a process of greedy pursuit. Simulation results indicate that the presented method outperforms both OMP and ESPRIT at different SNRs.
Array signal processing compressed sensing direction of arrival estimation matching pursuit algorithms sparse recovery.
Liu Yin Wu Shunjun Wu Mingyu Li Chunmao
National Lab of Radar Signal Processing, Xidian University, Xi’an, Shaanxi, China, 710071
国际会议
2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)
成都
英文
315-318
2011-10-24（万方平台首次上网日期，不代表论文的发表时间）