摘要
提出了一种用于空间相干源DOA估计的加权空间平滑算法(WSS, weighted spatial smoothing)。常规的空间平滑算法没有利用子阵输出的互相关信息,而且对相干信源的分辨力较差。WSS算法充分利用了子阵输出的自相关信息和互相关信息,将主阵协方差矩阵的所有子阵阵元数阶的子矩阵进行加权平均,以期提高常规空间平滑算法的分辨性能。文中以加权平滑后等效的信源协方差矩阵的对角化为约束条件,推导了加权矩阵的理论表达式。计算机仿真结果表明,WSS算法与常规空间平滑算法相比具有更高的分辨性能和更低的信噪比门限。特别是在子阵划分较多时其优越性更加明显。
In this paper an improved spatial smoothing technique for direction-of-arrival estimation of coherent signals is proposed,which we call 搘eighted spatial smoothing (WSS)? Conventional spatial smoothing (SS) technique ignores the cross correlation information of subarray output with an inferior resolving ability for coherent signals . In order to decorrelating the coherent signals more completely, WSS technique takes full advantage of the auto-correlation and cross-correlation information of subarray output and makes a weighted sum of all sub-matrixes of array covariance matrix to form an equivalent subarray covariance matrix. The formula for the possible weight matrix is also derived based on the criterion that the smoothed sources covariance matrix is a diagonal matrix. Simulation results demonstrate that the WSS technique possesses a better revolving ability and a lower SNR threshold than conventional SS technique for DOA estimation of coherent signals,especially in the case that the size of subarray is small.
出处
《通信学报》
EI
CSCD
北大核心
2003年第4期31-40,共10页
Journal on Communications
基金
全国高等学校优秀青年教师教学科研奖励计划(TRAPOYT)资助
