基于变换域张量的机载阵列DOA和极化参数估计  

Transform domain based tensor algorithm for estimating DOA and polarization parameters of airborne array

作　　者：张晓文 廖桂生[1] 杨志伟[1] 杨春晓 ZHANG Xiaowen;LIAO Guisheng;YANG Zhiwei;YANG Chunxiao(National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China)

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

出　　处：《系统工程与电子技术》2019年第5期986-991,共6页Systems Engineering and Electronics

基　　金：国家自然科学基金(61671352;61231017)资助课题

摘　　要：针对强杂波背景下多目标回波的参数估计问题,现有的基于长矢量的多重信号分类(long vector multiple signal classification,LV-MUSIC)法精度下降,基于张量的MUSIC(tensor MUSIC,T-MUSIC)方法通道数不足,无法计算噪声子空间投影矩阵。因此提出基于变换域张量的MUSIC方法。算法利用张量结构,在时域分离不同多普勒频率的信号,分别估计各多普勒通道的回波参数。相比于LV-MUSIC和T-MUSIC,所提算法避免了多目标背景下自由度不足导致的目标分辨力下降的问题,并且能获得更高精度的参数估计。仿真实验证明,所提算法有更高的目标分辨能力,在低信噪比条件下仍保持良好的性能。When estimating parameters of multiple target echoes with strong ground clutter, the precision of the long vector multiple signal classification (LV-MUSIC) decreases, and the noise subspace projection matrix in tensor MUSIC (T-MUSIC) cannot be calculated because of the deficiency of the channel. Since then, a transform domain based tensor of MUSIC algorithm (T 2-MUSIC) is proposed. The algorithm makes use of the tensor structure to separate signals in time domain and estimates parameters in each doppler channel. Compared with LV-MUSIC and T-MUSIC, the proposed algorithm can ensure resolvable target number on multiple targets condition with the loss of degree of freedom, while achieves a higher parameter estimation precision. The simulations exhibit the enhanced resolution ability of T 2-MUSIC and the higher precision under the condition of low signal-to-noise ratio.

关 键 词：极化敏感阵列 波达角参数估计 极化参数估计 张量 多重信号分类 

分 类 号：TN958[电子电信—信号与信息处理]