首先将信号源的距离和到达角信息进行分离,构造出一个新的方向矩阵;利用此新的方向矩阵构造一个二阶协方差矩阵,并通过仅仅一维搜索获得了所有信号源的到达角.然后基于已得到的到达角信息,结合多重信号分类(MUSIC)算法,通过一维搜索将具有相同到达角的近场源和远场源进行了分离.最后,基于已获得的近场源的到达角信息,估计出了所有近场源的距离参数.此算法不需要构造高阶累计量、二维搜索和参数配对;所有的实现过程仅需一维搜索,计算量小,实现简便.数值实验证明了所提出算法的有效性.
By separating the range and direction of arrival (DOA) information of the mixed sources, a new array steering vector was obtained. And then based on the new array steering vector and multiple signal classification (MUSIC), all DOAs of the mixed sources were obtained through only one-dimen- sional search. The near-field sources, which had the same DOA as the near-field sources, was separa- ted from the far-field sources by the estimated DOAs. Finally, by means of the estimated DOAs of all near-field sources, the range parameter of each near-field source was obtained. The algorithm needs neither high-order statistics nor two-dimensional search (only one-dimensional search), and does not need pairing parameters too. For by means of only one-dimensional search, the algorithm has low computational cost. Numerical experiment results show the performance of the algorithm.