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嵌套阵的疏密子阵融合波达方向估计方法

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为有效利用嵌套阵包含疏密子阵的几何结构以提高估计性能,本文提出一种在 2 子阵上分别测向再融合的波达方向估计方法.通过理论分析和实际案例阐明融合嵌套阵的两子阵测向结果可以消除信源角度估计模糊,且不会出现互质阵解模糊时伴随的匹配错误.利用无需谱峰搜索的求根多重信号分类方法在嵌套阵 2 子阵上求解测向结果,若稀疏子阵间距为N倍半波长,推导出对其复根开N次方可获含模糊角的高精度估计,再结合最小方差准则与精度较低但无模糊的密集子阵测向结果进行融合,最终得到高精度的波达方向估计.与嵌套阵已有算法相比,该算法提高了波达方向估计精度和分辨率,由于无需 2 子阵协方差降低了计算量,且能够支持嵌套阵的分布式配置.仿真结果验证了所提算法的有效性.
Direction of arrival estimation method by fusing sparse and dense subarrays of nested array
In order to improve estimation performance by effectively using the geometric structure of nested arrays containing sparse and dense subarrays,this paper proposes a DOA estimation method by finding directions on two subarrays and then merging them.Through theoretical analysis and practical cases,the results can clarify whether the direction finding results of two subarrays of the nested array can eliminate the ambiguity of source angle estima-tion.The results also determined whether matching errors accompanied the ambiguity resolution of the coprime ar-ray.First,the root-MUSIC method without peak search is used to solve the direction finding results on two subar-rays of nested arrays.Then,for the sparse subarray with N times the half-wavelength spacing between elements,it is deduced that the complex root can be opened for N times,thus obtaining a high-precision estimation with an am-biguity angle.Finally,the high-precision DOA estimation is obtained by combining the minimum variance criterion with the direction finding results of dense subarrays with low precision but no ambiguity.Compared with the existing algorithms of the nested array,this algorithm improves the accuracy and resolution of DOA estimation and reduces the computational complexity because it does not need the covariance of two subarrays.Furthermore,it can support the distributed configuration of nested arrays.Simulation results verify the effectiveness of the proposed algorithm.

nested arrayroot-MUSICvariance fusionsparse and dense subarraysdirection of arrival estimationsparse subarraydense subarrayambiguity resolution

王娜、赵宣植、刘增力、侯书画

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昆明理工大学 信息工程与自动化学院,云南 昆明 650504

嵌套阵列 求根多重信号分类 方差融合 疏密子阵 波达方向估计 稀疏子阵 密集子阵 解模糊

国家自然科学基金项目

61271007

2024

哈尔滨工程大学学报
哈尔滨工程大学

哈尔滨工程大学学报

CSTPCD北大核心
影响因子:0.655
ISSN:1006-7043
年,卷(期):2024.45(3)
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