现代电子技术2026，Vol.49Issue(17)：1-7,7.DOI:10.16652/j.issn.1004-373X.2026.17.001
基于多变换域特征信息的雷达波形匹配方法
Radar waveform matching method based on multi-transform-domain feature information
摘要
Abstract
In view of the degradation in waveform matching accuracy caused by noise interference and the limited representational capacity of single-transform-domain features,this paper proposes a multi-transform-domain feature fusion solution.Firstly,it constructs a three-channel joint representation by simultaneously extracting noise-resistant bispectral features,Hilbert marginal spectra suitable for analyzing non-stationary waveforms,and distinctive ambiguity function representative slices,thereby overcoming the incompleteness of single features.Secondly,a lightweight network with dual-attention mechanisms is designed to achieve adaptive feature weighting and noise suppression.Finally,a sliding window mechanism is employed to overcome phase alignment challenges.This approach establishes a technical chain of"multi-domain feature fusion-attention-based noise suppression-matching and localization".Experiments show that compared with the traditional ResNet method,the accuracy rate of the proposed method is improved by 4.71%in low SNR environment,and the proposed method can realize accurate matching in high SNR environment.Regarding matching speed,it reduces the time required for 100 training epochs by 46.5%compared to CNN.The proposed method has a wide engineering application prospect in the field of radar waveform detection and reconnaissance.关键词
多变换域特征/注意力机制/波形匹配/低信噪比环境/轻量化网络/滑动窗口/特征融合Key words
multi-transform-domain feature/attention mechanism/waveform matching/low SNR environment/lightweight network/sliding window/feature fusion分类
信息技术与安全科学引用本文复制引用
侯云皓,戴永寿,孙伟峰,张超,张鹏..基于多变换域特征信息的雷达波形匹配方法[J].现代电子技术,2026,49(17):1-7,7.基金项目
国家自然科学基金项目(42274159) （42274159）
山东省自然科学基金面上项目(ZR2024MF056) （ZR2024MF056）
