南京邮电大学学报（自然科学版）2026，Vol.46Issue(2)：1-10,10.DOI:10.14132/j.cnki.1673-5439.2026.02.001
基于Wi-Fi信号特征增强的跨域人体行为感知方法
Feature-augmentation-based cross domain human activity recognition using Wi-Fi signals
摘要
Abstract
Wi-Fi devices are easy to deploy and widely available,making Wi-Fi signals an attractive me-dium for wireless sensing.In particular,Wi-Fi-based human activity recognition has shown great poten-tial in smart homes and human-computer interaction applications.However,existing approaches usually treat channel state information(CSI)merely as a time series,neglecting variations across subcarriers,and often suffer from poor generalization in cross-domain scenarios.To address these issues,this paper proposes a cross-domain behavior recognition framework based on adaptive multi-dimensional feature en-hancement with domain feedback,termed DFAE-Fi.The proposed framework jointly models the temporal and channel characteristics of CSI through a time-frequency feature encoder,and introduces a domain feedback-driven feature enhancement mechanism that adaptively adjusts attention weights according to CSI statistical properties and domain discrepancies.By establishing feedback connections from the do-main discriminator to the feature extractor,DFAE-Fi enables collaborative optimization of feature en-hancement and domain adaptation.In addition,a discriminative feature loss and a dual-path training strategy are incorporated to further improve feature separability.Experimental results on public datasets demonstrate that the proposed method consistently outperforms existing approaches across various cross-domain scenarios.关键词
无线感知/人体行为识别/域适应/Wi-Fi信号Key words
wireless sensing/activity recognition/domain adaption/Wi-Fi signals分类
信息技术与安全科学引用本文复制引用
夏文超,陈安,刘哲鹏,赵海涛,朱洪波..基于Wi-Fi信号特征增强的跨域人体行为感知方法[J].南京邮电大学学报（自然科学版）,2026,46(2):1-10,10.基金项目
国家自然科学基金青年基金(62201285)资助项目 （62201285）
