基于动态加权均匀圆阵的无人机鲁棒测向方法

doi:10.12305/j.issn.1001-506X.2026.08.02

Abstract

Abstract:

To address the high-precision and strong robustness requirements of unmanned aerial vehicle (UAV) direction finding, a robust direction-finding method based on a dynamic weighted uniform circular array (UCA) is proposed. Building upon the UCA structure, the method iteratively calculates the residual variance of the phase difference for each baseline to evaluate the impact of noise on each baseline in real time. By integrating the influence of baseline length on direction-finding resolution, it dynamically constructs a weight matrix to optimize the direction estimation process. Experimental results demonstrate that in a complex Gaussian-pulse mixed noise environment, the proposed method significantly suppresses strong noise interference, achieves high-precision direction finding, and exhibits millisecond-level real-time performance along with excellent robustness, providing reliable technical support for real-time UAV monitoring and tracking in low-altitude security systems.

Key words: direction finding of unmanned aerial vehicle, uniform circular array (UCA), dynamic weighting, phase interferometer

CLC Number:

TN 971.+1

Min HUANG, Zhaorui LI, Huixian SUN, Xiang NI. Robust direction finding method for UAV based on dynamic weighted UCA[J]. Systems Engineering and Electronics, 2026, 48(8): 2520-2525.

Figures/Tables 7

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References 15

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条件类别	参数	值/范围	说明
阵列结构	阵元数量	15	均匀分布
阵列结构	半径	$\lambda /\left[ {4\sin (\text {π} /M)} \right]$	满足无模糊
信号特征	信号中心频率/GHZ	5.8	参考大疆M300系列
	信号带宽/MHZ	10	窄带信号
	快拍数	500	时域采样点数
噪声模型	脉冲噪声出现概率	0~0.4	鲁棒性分析变量
噪声模型	强度比	1000	固定基准值
入射信号	方位角/（°）	150	无人机飞行方向
入射信号	俯仰角/（°）	60	低空爬升/降落姿态
算法参数	最大迭代次数	10	收敛保障
算法参数	收敛阈值/（°）	0.01	实时保障
评估设置	蒙特卡罗实验次数	1000	稳定性保障
评估设置	SNR/dB	−5~20	步长1 dB

算法	SNR/dB
算法	−5	0	5	10
广义最小二乘法	0.051	0.024	0.022	0.021
现有迭代加权法	0.258	0.143	0.103	0.083
本文方法	0.464	0.295	0.208	0.178

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Robust direction finding method for UAV based on dynamic weighted UCA

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