互耦及脉冲噪声下基于稀疏重构的鲁棒DOA估计算法

doi:10.12305/j.issn.1001-506X.2025.08.03

摘要/Abstract

摘要：

针对互耦效应和脉冲噪声并存环境下的波达方向（direction of arrival，DOA）估计问题，提出一种结合M估计与稀疏重构的算法。首先，为了消除互耦效应的影响，依据互耦矩阵的托普利兹结构进行恒等变形，得到了不含未知互耦系数的字典。随后，为了使算法能适应高斯噪声和不同强度的脉冲噪声，将位置得分函数表示为高斯位置得分函数和一系列非线性函数的线性组合，利用噪声样本估计线性组合系数从而建立损失函数。最后，采用迭代硬阈值算法进行稀疏重构，并通过改进信号更新策略提高正确收敛的概率。仿真结果表明，所提算法能有效抑制互耦效应和脉冲（高斯）噪声的干扰，同时相较已有算法在低信噪比、强脉冲特性下的性能有显著提升。

关键词: 波达方向估计, 互耦, 脉冲噪声, 稀疏重构, M估计, 迭代硬阈值

Abstract:

To deal with the problem of direction of arrival （DOA） estimation in the presence of mutual coupling and impulsive noise, an algorithm that combines M-estimate and sparse reconstruction is proposed. Firstly, a dictionary without unknown mutual coupling coefficients is obtained through identical deformation based on the Toeplitz structure of the mutual coupling matrix to eliminate the influence of mutual coupling effect. Subsequently, in order to enable the algorithm to adapt to Gaussian noise and impulsive noise of different intensities, the location score function is expressed as a linear combination of Gaussian location score function and a series of nonlinear functions, and the loss function is established with an estimate of linear combination coefficients with noise samples. Finally, the iterative hard thresholding algorithm is utilized for sparse reconstruction, and an improved strategy for signal update is employed to increase the probability of correct convergence. Simulation results show that the proposed method can effectively suppress mutual coupling effect and impulsive （Gaussian） noise, and it outperforms the existing algorithms at low signal to noise ratios and strong impulse characteristics.

Key words: direction of arrival （DOA） estimation, mutual coupling, impulsive noise, sparse reconstruction, M-estimate, iterative hard thresholding

中图分类号:

TN 911.23

何从, 刘帅, 闫锋刚, 金铭. 互耦及脉冲噪声下基于稀疏重构的鲁棒DOA估计算法[J]. 系统工程与电子技术, 2025, 47(8): 2444-2453.

Cong HE, Shuai LIU, Fenggang YAN, Ming JIN. Robust DOA estimation algorithm in the presence of mutual coupling and impulsive noise based on sparse reconstruction[J]. Systems Engineering and Electronics, 2025, 47(8): 2444-2453.

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