分布式nested阵列及其高精度DOA估计  

High accuracy DOA estimation using separated nested array

作　　者：王毅[1] 陈伯孝[1] 杨明磊[1] 郑桂妹[1] 

机构地区：[1]西安电子科技大学雷达信号处理国家重点实验室,陕西西安710071

出　　处：《系统工程与电子技术》2015年第2期253-258,共6页Systems Engineering and Electronics

基　　金：国家自然科学基金(61001209;61101244);中央高校基本科研业务费专项资金(K5051202038)资助课题

摘　　要：为了进一步提高分布式阵列的自由度和分辨力,提出一种分布式nested阵列。该阵列将nested阵列作为分布式阵列的子阵。基于Khatri-Rao积,nested子阵可提高整个阵列的自由度。分布式nested阵列以较少的阵元数及硬件成本实现大的孔径和较高的分辨力,而且提高了目标波达方向(direction of arrival,DOA)估计的精度。并利用基于Khatri-Rao积的空间平滑酉旋转不变子空间(estimation of signal parameters via rotational invariance techniques,ESPRIT)算法进行DOA估计。其先对协方差矩阵向量化提高自由度,然后利用空间平滑对新数据协方差矩阵进行秩恢复,最后使用双尺度酉ESPRIT算法得到DOA估计。仿真结果证明所提方法的有效性。To further improve the degrees of freedom and resolution of separated coherent arrays, a novel separated nested array is proposed. The nested arrays are used as the subarrays of the separated array. Based on the Khatri-Rao product, the nested subarrays can improve the degrees of freedom of the separated nested array. The separated nested array possesses large aperture and high resolution with low hardware cost and improves di- rection of arrival（DOA）estimation accuracy. The spatial smoothing unitary estimation of signal parameters via rotational invariance techniques（ESPRIT）based on the Khatri-Rao product is proposed to implement the DOA estimation. The covariance matrix is vectorized to improve the degrees of freedom and the spatial smoothing is used to build up the rank of the new covariance matrix, and then the DOA estimation is obtained using the dual- size unitary ESPRIT algorithm. Simulation results are given to verify the effectiveness of the proposed method.

关 键 词：分布式nested阵列 KHATRI-RAO积 酉旋转不变子空间 波达方向 

分 类 号：TN958[电子电信—信号与信息处理]