Ultra wide band radar gait recognition based on slow-time segmentation

被引：3
作者：
Zhou J.-H. [1 ]
Wang Y.-C. [1 ]
Tong J.-P. [1 ]
Zhou S.-Y. [1 ]
Wu X.-F. [2 ]
机构：
[1] College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou
[2] Hangzhou Magnet Intelligent Technology Co. Ltd, Hangzhou
来源：
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2020年 / 54卷 / 02期
关键词：
Free space; Histogram of oriented gradient; Long short-term memory network; Segmentation; Slow-time; Ultra wide band (UWB) radar;
D O I：
10.3785/j.issn.1008-973X.2020.02.009
中图分类号：
学科分类号：
摘要：
An algorithm for free space gait recognition using ultra wide band (UWB) radar was proposed in order to solve the problems of privacy leakage caused by cameras and intrusiveness caused by wearable devices in the indoor monitoring, and to relax the restriction on walking conditions in traditional radar gait recognition algorithms. The radar gait signal reflected from the walking target is segmented along the slow-time axis to generate a series of sub-signals. For each sub-signal, the Fourier transform is performed on range bins to obtain a range-Doppler map. These range-Doppler maps temporally correlate each other. The features of a set of range-Doppler maps belonging to the same gait signal are extracted using the histogram of oriented gradient algorithm, and the resulting features are modeled by long short-term memory networks to obtain the final classification result of the target identity. The experiment was carried out in an empty indoor environment, and the accuracy of gait classification for four individuals was 79.10%. Results show that the proposed algorithm has a certain discrimination ability to different individual's gait in free space. © 2020, Zhejiang University Press. All right reserved.
引用
收藏
页码：283 / 290
页数：7
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