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引用本文:刘宁庄,侯志凯,符渭波,田海波. 基于降维累积量和矩阵重构的相干DOA估计[J]. 雷达科学与技术, 2026, 24(1): 31-41.[点击复制]
LIU Ningzhuang, HOU Zhikai, FU Weibo, TIAN Haibo. Coherent DOA Estimation Based on Reduced‑Dimensional Cumulants and Matrix Reconstruction[J]. Radar Science and Technology, 2026, 24(1): 31-41.[点击复制]
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基于降维累积量和矩阵重构的相干DOA估计
刘宁庄,侯志凯,符渭波,田海波
1. 西安科技大学电气与控制工程学院, 陕西西安 710000;2. 西安科技大学通信与信息工程学院, 陕西西安 710000;3. 西安科技大学机械工程学院, 陕西西安 710000
摘要:
针对复杂电磁环境中因低信噪比、快拍采样数据不足、非高斯杂波干扰及多径传播效应等导致的波达方向(Direction of Arrival, DOA)估计性能退化问题,本文提出了一种基于降维高阶累积量与低秩矩阵重构的多源相干信号的DOA估计算法。首先通过构建四阶累积量矩阵扩展阵列孔径,抑制高斯噪声,提升欠定条件下的信号自由度;随后采用高效的降维策略,显著降低计算复杂度;最后通过交替方向乘子法求解低秩约束下的Toeplitz协方差矩阵重构问题,实现了复杂环境下多源相干信号的高精度定位。实验结果表明,本算法在低信噪比及少快拍数下对多源相干信号依然有出色的估计性能,兼具高精度和强抗干扰特性,有良好的工程实用价值。
关键词:  阵列信号处理  相干DOA估计  高阶累积量  降维变换  交替方向乘子法
DOI:DOI:10.3969/j.issn.1672-2337.2026.01.004
分类号:TN911.7
基金项目:国家自然科学基金(52174149);陕西省重点研发计划项目(2022GY?241)
Coherent DOA Estimation Based on Reduced‑Dimensional Cumulants and Matrix Reconstruction
LIU Ningzhuang, HOU Zhikai, FU Weibo, TIAN Haibo
1. College of Electrical and Control Engineering, Xi'an University of Science and Technology, Xi'an 710000, China;2. College of Communication and Information Engineering, Xi'an University of Science and Technology, Xi'an 710000,China;3. College of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710000, China
Abstract:
In this paper,a direction of arrival (DOA) estimation method for multi?source coherent signals based on reduced?dimensional higher?order cumulants and low?rank matrix reconstruction is proposed to improve the performance of DOA estimation in radar systems caused by low signal?to?noise ratio (SNR), insufficient snapshot sampling data, non?Gaussian clutter interference, and multipath propagation effects in complex electromagnetic environments. Firstly, by constructing a fourth?order cumulant matrix, the array aperture is expanded to suppress Gaussian noise. Then, an efficient reduced?dimensional strategy is employed to reduce computational complexity. Finally, the alternating direction method of multipliers is used to solve the reconstruction problem of Toeplitz covariance matrix under low?rank constraints, achieving high?precision localization of multi?source coherent signals in complex environments. Experimental results demonstrate that the proposed algorithm maintains excellent estimation performance for multi?source coherent signals under low SNR and limited snapshots, combining high accuracy and strong anti?interference capabilities.
Key words:  array signal processing  coherent direction of arrival (DOA) estimation  higher‑order cumulants  reduced‑dimensional transformation  alternating direction multiplier method

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