相干信源DOA估计的非对称加权空间平滑差分算法

提出了相干信源DOA估计的非对称加权空间平滑差分(UWSSD)算法。在空间平滑差分运算的基础上,对各子阵协方差矩阵采用非对称权值加权处理,破坏差分矩阵的负反对称特性,从而使信源差分协方差矩阵恢复为满秩。差分矩阵中不含相关噪声及非相关源信息,可利用它分辨相关及相干信源,而利用传统子空间算法分辨非相干信源,从而重复利用阵列接收数据,可分辨更多信源。通过分析差分矩阵的特点,提出了一种无需矩阵特征分解的快速算法。仿真结果表明,UWSSD算法具有较强的噪声抑制能力及信源过载能力。

Unsymmetrical weighted spatial smoothing difference algorithm for DOA estimation of coherent sources

Unsymmetrical weighted spatial smoothing difference(UWSSD) algorithm,a new method for the DOA estimation of coherent sources is proposed.Based on the spatial smoothing difference technique,the UWSSD algorithm uses unsymmetrical weights in the subarray covariance matrices,destroys the negative contrary symmetrical characteristic and makes the source covariance matrix full rank.The difference matrix has no information of correlated noise and uncorrelated sources,which may be used to estimate the correlated or coherent sources,and the uncorrelated sources are estimated by conventional subspace-based methods,thus more sources can be estimated.By analyzing the difference matrix,a rapid method without eigen-decomposition is given.Computer simulation results demonstrate that the UWSSD method possesses a better resistance capability of correlated noise as well as estimates more sources.