极高频率
计算机科学
遥感
雷达
融合
传感器融合
雷达跟踪器
连续波雷达
雷达工程细节
雷达信号处理
信号处理
脉冲多普勒雷达
杂乱
雷达探测
稳健性(进化)
三维雷达
雷达成像
雷达系统
波浪雷达
电子工程
预警雷达
雷达锁定
实时计算
雷达配置和类型
大气模式
毫米
声学
时频分析
信噪比(成像)
连续波
作者
Chengjian Xing,Xiaolu Zeng,Xiaopeng Yang,Yu Liu,Huimin Hao,Miao Liu
标识
DOI:10.1109/jiot.2026.3686498
摘要
Non-contact vital sign sensing has attracted increasing attention from both academia and industry. Millimeter-wave radar-based respiration sensing provides high accuracy but suffers from a limited field of view and strong dependence on target position and orientation, which restricts its practical deployment. In contrast, Wi-Fi-based sensing provides wide coverage and great resilience over device setup, yet its respiration estimation accuracy under ideal conditions is generally inferior to that of millimeter-wave radar. Consequently, the robustness of single-modal approaches in practical scenarios remains limited due to the inherent drawbacks of each system. This paper presents a fusion-based respiration monitoring system that integrates millimeter-wave radar and Wi-Fi signals. By jointly exploiting the high precision of millimeter-wave radar and the wide-area sensing capability of Wi-Fi, robust respiration monitoring is achieved in practical bedroom environments. To effectively utilize heterogeneous signals, a fusion decision scheme is designed to adaptively determine the necessity of signal fusion. Furthermore, a multi-modal signal fusion method based on multivariate signal processing is proposed to jointly extract the common respiration components shared across different modalities. Extensive experimental results demonstrate that the proposed system, FuseRes, can robustly and accurately estimate respiration in complex real-world scenarios, supporting stable non-contact vital sign monitoring and facilitating practical deployment.
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