多子阵互耦影响下的非圆信号自校正算法  

Auto-Calibration Method for Noncircular Sources in the Presence of Mutual Coupling of Multiple Subarrays

作　　者：尹洁昕 吴瑛[1] 王鼎[1] 

机构地区：[1]解放军信息工程大学信息系统工程学院,河南郑州450002

出　　处：《电子学报》2015年第9期1696-1704,共9页Acta Electronica Sinica

基　　金：国家自然科学基金(No.61201381);信息工程学院未来发展基金(No.YP12JJ202057)

摘　　要：针对多子阵互耦影响下的非圆信号波达方向(Sirection-Of-Arrival,DOA)估计问题,给出了一种针对最大非圆率信号的互耦自校正算法.该算法利用均匀线阵互耦矩阵的带状、对称Toeplitz性和多子阵互耦矩阵的块状对角特性,能够与传统的互耦秩减估计器一样避免多维搜索和迭代运算.并且通过结合信号的非圆特性来扩展数据模型,使得其估计精度较传统的互耦秩减估计算法有明显提升,可分辨信源数也有所增加.对该算法的理论性能进行研究,分析了其对未知参数的可辨识性必要条件,并基于最大非圆率信号模型给出了相应的克拉美罗界(Cramer-Rao Bound,CRB).仿真结果表明,该算法较传统的互耦秩减估计算法在低信噪比、小快拍数下有更强的鲁棒性.The direction-of-arrival （DOA）estimation method for noncircular sources with maximum noncircularity rate in multiple subarrays is proposed when there exists mutual coupling between sensors of each subarray.Based on the banded and sym-metric Toeplitz character of the coupling matrix of uniform linear arrays （ULAs）and the block diagonal character of the coupling matrix of multiple subarrays,the proposed method can avoid multidimensional search and iterative computation like the conventional rank reduction estimator （RARE）.We extend the data model by using the noncircular feature of the sources,and thus the proposed method outperforms the conventional RARE in terms of estimation accuracy and the number of sources that can be distinguished. The performance study provides a necessary condition for unique estimation,and the expression of noncircular Gaussian Cram＆#233;r-Rao bound （CRB）matrix for DOAs is presented.The simulation results illustrate that the proposed algorithm is more robust than the conventional RARE with respect to lower signal-to-noise ratio and fewer number of samplings.

关 键 词：多子阵 互耦 波达方向估计 最大非圆率信号 克拉美罗界 

分 类 号：TN911.7[电子电信—通信与信息系统]