基于双向传播算子的互质面阵二维波达方向估计

doi:10.3969/j.issn.0372-2112.2019.03.009

摘要/Abstract

摘要： 针对谱峰搜索的二维波达方向估计中现有算法复杂度高，精度受搜索间隔影响较大的问题，给出了一种双向传播算子的互质面阵二维波达方向估计算法，实现了俯仰角和方位角的低复杂、高精度、无模糊联合估计.该方法首先将互质阵列引入到二维波达方向估计中，构造互质平面阵模型，然后采用两次旋转不变传播算子方法计算出不同阵列流型方向上的旋转因子矩阵，根据旋转因子矩阵解算出目标信号的俯仰角和方位角，同时利用互质理论消除了稀疏阵列角度估计的不确定性，证明了互质阵列模型下采用双向传播算子方法进行俯仰角和方位角估计的无模糊性.对算法的复杂度进行理论分析，并给出了平面阵列角度估计的克拉美罗界推导.理论分析与仿真结果表明，算法不需要进行角度匹配和谱峰搜索，在相同条件下的均方根误差性能优于均匀平面阵的多重信号分类算法，并且以较低的复杂度无模糊的达到了高维网格搜索的精度.

关键词: 互质面阵, 传播算子, 波达方向, 克拉美罗界

Abstract: In the existing two-dimensional direction-of-arrival (DOA) estimation algorithms based on spectral peak search,the complexity is high and the accuracy is greatly influenced by the search interval.To overcome these problems,this paper examines a two-dimensional DOA estimation with coprime rectangular array using bi-directional propagator method,which realizes a low complexity,high accuracy,unambiguous for 2-D estimation.Firstly,this algorithm introduces coprime array into 2-D DOA estimation,and constructs a coprime rectangular array model.The two rotation factor matrices along the different directions for propagator method can be got,the elevation angle and azimuth angle for the sources can be obtained from the rotation factor matrices.Further more,the multi values of sparse array are eliminated by using coprime theory,and the proof of unambiguous for two-dimensional DOA estimation under the coprime array model is provided.This paper also analyzes the complexity and gives the Cramer Rao lower bounds (CRB) of coprime rectangular array.Theoretical analysis and simulation results show that this algorithm does not need to angle matching and spectrum peak search,under the same conditions,the root mean square error (RMSE) performance is better than the multiple signal classification (MUSIC) algorithm of uniform rectangular array.At the same time,the proposed algorithm can reach the same accuracy of high dimensional grid search with low complexity and without ambiguity.

Key words: coprime rectangular array, propagator method, direction-of-arrival (DOA), Cramer Rao lower bounds (CRB)

中图分类号:

TN911.7

张彦奎, 王大鸣, 耿卫, 巴斌, 许海韵, 代正亮. 基于双向传播算子的互质面阵二维波达方向估计[J]. 电子学报, 2019, 47(3): 576-583.

ZHANG Yan-kui, WANG Da-ming, GENG Wei, BA bin, XU Hai-yun, DAI Zheng-liang. Two-Dimensional DOA Estimationwith Coprime Rectangular Array Using Bi-directional Propagator Method[J]. Acta Electronica Sinica, 2019, 47(3): 576-583.

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