雷达
计算机科学
雷达成像
连续波雷达
算法
反褶积
杂乱
计算机视觉
人工智能
电信
作者
Fulai Liang,Hao Lou,Yang Zhang,Ling Hao,Xiao Fang Yu,Qiang An,Zhao Li,Jianqi Wang
出处
期刊:Measurement
[Elsevier BV]
日期:2022-04-01
卷期号:195: 111074-111074
被引量:1
标识
DOI:10.1016/j.measurement.2022.111074
摘要
Radar-based life imaging technology has been widely applied in both civilian and military applications. Wall penetration attenuation degrades the signal-to-clutter-and-noise ratio (SCNR) and radar portability restricts the spatial resolution of the high-dimensional image. In this study, we constructed a portable linear-frequency continuous-wave (LFMCW) multiple-input multiple-output (MIMO) radar system, and we presented a novel high-dimensional imaging framework. We combined the maximum spectrum peak, fourth-order cumulant (FOC) and 3D coherent factor (CF) to enhance vital signs based on attention mechanism. We improve resolution by deconvolution algorithm using the data from a human dummy. Visualization-enhanced 4D point clouds images were created by mapping micro-doppler-frequency to color. We employed a series of experiments to validate the proposed method, including human and beagle imaging in free space, and short-range and long-range (16 m) human imaging through a wall. These high-dimensional imaging results validated the portable radar system’s potential in detection, identification, interpretation of human targets.
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