Multi-domains based Human Activity Classification in Radar

Li, Z., Fioranelli, F. , Yang, S. , Zhang, L. , Romain, O., He, Q., Cui, G. and Le Kernec, J. (2021) Multi-domains based Human Activity Classification in Radar. In: IET International Radar Conference 2020, Chongqing City, China, 4-6 Nov 2020, pp. 1744-1749. ISBN 9781839535406 (doi: 10.1049/icp.2021.0557)

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223724.pdf - Accepted Version



In human activity recognition (HAR) based on radar, significant research exists on statistical features extracted from the spectrogram (μD), whereas the research which considers other domains is less developed. This paper is aimed to investigate three domains of radar data: μD, Cadence Velocity Diagram (CVD), and range-time (RT) information, evaluating which ones are best suited to classify specific activities. In addition, information fusion is applied to enhance classification accuracy and compare it with the results of single domain approach. Based on the previous results, a hierarchical structure is proposed to improve the performance of classification further. The preliminary results show that different domains have distinctive sensitivity to specific activities. RT information is sensitive to the moving target crossing range bins, while CVD is more sensitive to body movement. The μD is more balanced, which means it can observe both moving targets and body movements. Furthermore, improvement in accuracy is approximately 6-23 % using feature-level fusion. A hierarchical classification approach is also investigated, which has accuracy in the order of approximately 92 %.

Item Type:Conference Proceedings
Additional Information:The authors would like to thank the British Council 515095884 and Campus France 44764WK – PHC Alliance France-UK for their financial support.
Glasgow Author(s) Enlighten ID:Romain, Professor Olivier and Zhang, Professor Lei and Yang, Dr Shufan and Fioranelli, Dr Francesco and Le Kernec, Dr Julien and Li, Zhenghui
Authors: Li, Z., Fioranelli, F., Yang, S., Zhang, L., Romain, O., He, Q., Cui, G., and Le Kernec, J.
College/School:College of Science and Engineering
College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
Copyright Holders:Copyright © 2021 The Institution of Engineering and Technology
First Published:First published in IET International Radar Conference 2020: 1744-1749
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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