独立源与相干源并存的信源数估计  

Source number estimation of coexisting uncorrelated and coherent sources

作　　者：毛维平[1] 李国林[2] 谢鑫[2] 王凌[1] 

机构地区：[1]海军航空工程学院研究生管理大队,山东烟台264001 [2]海军航空工程学院七系,山东烟台264001

出　　处：《系统工程与电子技术》2014年第3期422-428,共7页Systems Engineering and Electronics

基　　金：国家自然科学基金(60902054)资助课题

摘　　要：大多数子空间类谱估计算法,需要预先估计信源个数,而且当信号源相干或强相关时,不能直接应用基于信息论的估计方法。针对接收信号为独立源与相干源并存的情况,提出一种新的基于矩阵重构的信源数估计算法。算法利用各个阵元接收数据与参考阵元接收数据的互相关信息,构造一个Toeplitz等效协方差矩阵解相干。理论分析证明,相比于复信号解相干的常规Toeplitz矩阵重构方法,算法节省一半的阵列孔径,而且对噪声发散性有一定抑制作用。基于此构造矩阵采用特征子空间投影与特征值加权的方法构造判决函数来估计信源个数,仿真结果表明,算法在独立源和相干源并存的情况下,能准确估计出信源个数,性能优于空间平滑Akaike信息论准则法和空间平滑最小描述长度法。Detecting the source number is an important step to eigensubspace spatial spectrum estimation algorithms. Information theory methods are not applicable to cope with the situation where both uncorrelated and coherent sources exist. A novel method based on matrix reconstruction is proposed to solve this problem. A Toeplitz equivalent covariance matrix is reconstructed by using cross-correlation information of the receiv ing data from arrays. To some extent, the constructed matrix can reduce the spreading of the noise eigenval ues. Compared with the conventional method using the first vector of the covariance matrix to construct a de coherence Toeplitz matrix, the proposed algorithm has better de-coherence performance and avoids the loss of array physical aperture. Ultimately, the proposed algorithm utilizes weighted eigen subspace projection meth- od to estimate the source number. Computer simulation confirms that the algorithm can accurately estimate the number of sources mixed with uncorrelated and coherent sources and has better performance compared with spatial smoothing Akaike information criterion and spatial smoothing minimum description length algo rithms.

关 键 词：阵列天线 信源数估计 独立信源与相干信源 矩阵重构 特征子空间投影 

分 类 号：TN911.7[电子电信—通信与信息系统]