通信学报2025，Vol.46Issue(11)：87-103,17.DOI:10.11959/j.issn.1000-436x.2025208
基于HHO-VMD增强的稀疏循环自相关微弱信号检测方法
HHO-VMD enhanced sparse cyclic autocorrelation method for weak signal detection
摘要
Abstract
To address the challenge of detecting weak signals from non-cooperative sources in complex electromagnetic environments,a sparse cyclic autocorrelation detection method with enhancement using Harris Hawks optimization-based variational mode decomposition(HHO-VMD)was proposed.Firstly,based on the ray tracing method and a hybrid noise model,a target signal model was constructed in a complex electromagnetic environment.To address the issue that key features of weak target signals were submerged by noise and difficult to extract,HHO-VMD was proposed to en-hance the target signal features.To tackle the problem of ineffective extraction of subtle signal features under sampling conditions,a sparsity-constrained cyclic autocorrelation function was constructed to extract fine-grained signal features effectively.Finally,a peak amplitude correlation statistic at non-zero cyclic frequencies was derived for target and back-ground signals,and weak target detection was achieved using a binary hypothesis testing model.Simulations and experi-ments demonstrated that the proposed method has higher detection accuracy under low signal-to-noise ratio and small sample conditions.关键词
微弱信号检测/变分模态分解/循环自相关/稀疏度约束Key words
weak signal detection/variational mode decomposition/cyclic autocorrelation/sparsity constraint分类
信息技术与安全科学引用本文复制引用
李保珠,李龙辉,刘彤,张铮,姜文..基于HHO-VMD增强的稀疏循环自相关微弱信号检测方法[J].通信学报,2025,46(11):87-103,17.基金项目
国家自然科学基金资助项目(No.62071347)The National Natural Science Foundation of China(No.62071347) （No.62071347）
