基于SVD和Toeplitz的高效DOA估计算法  

A New and Efficient TSVD Algorithm for Estimating DOA(Direction of Arrival)

作　　者：陈绍炜[1] 魏盈盈[1] 冯晓毅[1] 

机构地区：[1]西北工业大学电子信息学院,陕西西安710129

出　　处：《西北工业大学学报》2010年第6期883-886,共4页Journal of Northwestern Polytechnical University

基　　金：航空科学基金(2008ZC53030)资助

摘　　要：文章通过对SVD和Toeplitz算法的研究,针对空间谱估计中的难点问题即相干信号的DOA估计,采用一种新的高效算法,即对信号协方差矩阵进行特征分解,利用最大特征向量构建1个具有Toeplitz性质的新矩阵,最后利用奇异值分解得到信号的波达方向。仿真实验证明,在低信噪比情况下(-10 dB),SVD算法已基本失效,Toeplitz算法误差达2°,而新算法的估计误差几乎为0。Aim.The introduction of the full paper reviews some references and then proposes our TSVD algorithm,which combines adroitly the SVD（singular value decomposition） algorithm with the Toeplitz algorithm.Sections 1 through 4 explain our TSVD algorithm.Section 2 briefs the SVD algorithm.Section 3 briefs the Toeplitz algorithm.The core of section 4 consists of：（1） we decompose the eigenvector of the coherent signal covariance matrix and obtain its maximum eigenvector value,with which we reconstruct a new matrix that possesses the properties of the Toeplitz algorithm;the new matrix is given in eq.（12）;（2） we decompose the singular value of the new matrix;the minimum eigenvector value,corresponding to the small singular values,constitutes noise subspace,while the maximum eigenvector value,corresponding to the large singular values,constitutes signal subspace;（3） we utilize eq.（8） in section 2 to search for the spectral peak,thus estimating the DOA of the incident signal.Section 5 simulates our TSVD algorithm with two numerical examples;the simulation results,presented in Figs.1 through 4,and their analysis show preliminarily that,compared with the conventional SVD and Toeplitz algorithms,our new algorithm produces more precise and stable estimations： when SNR（signal to noise ratio） is-10 dB,the SVD algorithm does not work,the estimation error of the Toeplitz algorithm is up to 20,but the estimation error of our new TSVD algorithm is close to 0.

关 键 词：波达方向 相干信号 奇异值分解 低信噪比 

分 类 号：TN911.4[电子电信—通信与信息系统]