Novel high-resolution DOA estimation using subspace projection method  

作　　者：SI Wei-jian LAN Xiao-yu ZOU Yan 

机构地区：[1]College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China [2]No. 91404 Army, Qinhuangdao 066000, China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2012年第4期110-116,共7页中国邮电高校学报（英文版）

基　　金：supported by the National Basic Research Program of China (61393010101-1)

摘　　要：The performance of multiple signal classification （MUSIC） algorithm with regard to solving closely spaced direction of arrivals （DOAs） depends strongly upon the signal-to-noise ratio （SNR） and snapshots. In order to solve this problem, a method by reconstructing the spatial spectrum function with both noise subspace and signal subspace is presented in this paper. The key idea is to apply the full information contained in covariance matrix and change the projection weights of steering vector on the noise and signal subspace by their revised eigenvalues, respectively. Comparing with the MUSIC algorithm, it does not increase any computational complexity either, and remarkably, it has the advantages of simultaneously reducing noise and keeping the high-resolution ability under low SNR and small sample sized scenarios. Simulation and experiment results are included to demonstrate the superior performance of the proposed algorithm.The performance of multiple signal classification （MUSIC） algorithm with regard to solving closely spaced direction of arrivals （DOAs） depends strongly upon the signal-to-noise ratio （SNR） and snapshots. In order to solve this problem, a method by reconstructing the spatial spectrum function with both noise subspace and signal subspace is presented in this paper. The key idea is to apply the full information contained in covariance matrix and change the projection weights of steering vector on the noise and signal subspace by their revised eigenvalues, respectively. Comparing with the MUSIC algorithm, it does not increase any computational complexity either, and remarkably, it has the advantages of simultaneously reducing noise and keeping the high-resolution ability under low SNR and small sample sized scenarios. Simulation and experiment results are included to demonstrate the superior performance of the proposed algorithm.

关 键 词：direction ＆arrival （DOA） multiple signal classification low SNR RESOLUTION subspace projection 

分 类 号：TN911.23[电子电信—通信与信息系统] O241.6[电子电信—信息与通信工程]