Multiple Stationary Human Targets Detection in Through-Wall UWB Radar Based on Convolutional Neural Network

被引:6
作者
Shi, Cheng [1 ,2 ,3 ]
Zheng, Zhijie [1 ,2 ,3 ]
Pan, Jun [1 ,2 ,3 ]
Ni, Zhi-Kang [1 ,2 ,3 ]
Ye, Shengbo [1 ,2 ]
Fang, Guangyou [1 ,2 ,3 ]
机构
[1] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100190, Peoples R China
[2] Chinese Acad Sci, Key Lab Electromagnet Radiat & Sensing Technol, Beijing 100190, Peoples R China
[3] Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, Beijing 100190, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 09期
基金
中国国家自然科学基金;
关键词
convolutional neural network; multiple stationary human targets; through-wall detection; ultra-wideband (UWB) impulse radar; RESPIRATION; IDENTIFICATION; ANTENNA; MOTION; RATES;
D O I
10.3390/app12094720
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Ultra-wideband (UWB) impulse radar is widely used for through-wall human detection due to its high-range resolution and high penetration capability. UWB impulse radar can detect human targets in non-line-of-sight (NLOS) conditions, mainly based on the chest motion caused by human respiration. The automatic detection and extraction of multiple stationary human targets is still a challenge. Missed alarms often exist if the detection method is based on the energy of the human target. This is mainly because factors such as the range of the target, the intensity of the respiratory movement, and the shadow effect will make a difference between the energy scattered by targets. Weak targets are easily masked by strong targets and thus cannot be detected. Therefore, in this paper, a multiple stationary human targets detection method based on convolutional neural network (CNN) in through-wall UWB impulse radar is proposed. After performing the signal-to-clutter-and-noise ratio (SCNR) enhancement method on the raw radar data, the range-slow-time matrix is fed into a six-layer CNN. Benefiting from the powerful feature extraction capability of CNN, the target point of interest (TPOI) can be extracted from the data matrix. The clustering algorithm is used to simplify the TPOIs to achieve accurate detection of multiple targets behind the wall. The effectiveness of the proposed method is verified by the experimental data.
引用
收藏
页数:19
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