摘要
该文采用均匀且稀疏分布的电磁矢量矩形阵列,针对相干目标提出了一种有效的2维波达角(DOA)估计算法,该算法通过增加相邻阵元的间隔来扩展阵列的有效孔径,从而提高算法的DOA估计性能。论文首先结合极化平滑算法和传播算子方法得到存在相位周期性模糊的方向余弦估计。为了解决模糊性问题,论文通过协方差矩阵平滑提出一种新的解相干预处理算法,由该算法得到的信号子空间包含矢量阵元的导向矢量,且不存在相位模糊,利用此特点实现去模糊处理,得到目标的DOA估计。仿真结果表明,与基于ESPRIT的孔径扩展算法相比,提出的算法能够实现相干目标的DOA估计,同时无需特征值或奇异值分解,有更低的运算量。
An efficient algorithm for multiple coherent sources’ two-dimensional Direction Of Arrival(DOA) estimation with a sparse uniform rectangular array of electromagnetic vector sensor(EmVS) is proposed.The algorithm can improve the DOA estimation performance by increasing the intervector sensor spacing to achieve aperture extension.The Polarization Smoothing Algorithm(PSA) is coupled with the propagator method(PM) to acquire cyclically ambiguous DOA estimates.In order to disambiguate the cyclic phase ambiguities,a novel pre-processing method is derived by Covariance Matrix Averaging(CMA) and identify the true DOA estimates from a set of cyclically ambiguous candidate estimates based on the vector sensor steering vector's characteristics.Comparing with the existing extended aperture-based direction finding method,the proposed algorithm can estimate the DOA of coherent sources,and requires no eigen-decomposition,hence,has a lower computational complexity.Monte-Carlo simulations are presented to verify the effectiveness of the proposed algorithm.
出处
《电子与信息学报》
EI
CSCD
北大核心
2010年第10期2511-2515,共5页
Journal of Electronics & Information Technology
关键词
阵列信号处理
波达方向估计
相干信号
极化敏感阵列
极化平滑算法
Array signal processing
Direction Of Arrival (DOA) estimation
Coherent source
Polarization sensitive array
Polarization smoothing algorithm