Ritchie, M;
Fioranelli, F;
Griffiths, H;
(2015)
Multistatic human micro-Doppler classification of armed/unarmed personnel.
IET Radar, Sonar & Navigation
, 9
(7)
pp. 857-865.
10.1049/iet-rsn.2014.0360.
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Abstract
Classification of different human activities using multistatic micro-Doppler data and features is considered in this paper, focusing on the distinction between unarmed and potentially armed personnel. A database of real radar data with more than 550 recordings from 7 different human subjects has been collected in a series of experiments in the field with a multistatic radar system. Four key features were extracted from the micro-Doppler signature after Short Time Fourier Transform analysis. The resulting feature vectors were then used as individual, pairs, triplets, and all together before inputting to different types of classifiers based on the discriminant analysis method. The performance of different classifiers and different feature combinations is discussed aiming at identifying the most appropriate features for the unarmed vs armed personnel classification, as well as the benefit of combining multistatic data rather than using monostatic data only.
Type: | Article |
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Title: | Multistatic human micro-Doppler classification of armed/unarmed personnel |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1049/iet-rsn.2014.0360 |
Publisher version: | http://dx.doi.org/10.1049/iet-rsn.2014.0360 |
Language: | English |
Additional information: | Copyright © The Institution of Engineering and Technology 2015. This paper is a preprint of a paper accepted by IET Radar, Sonar and Navigation and is subject to Institution of Engineering and Technology Copyright. When the final version is published, the copy of record will be available at IET Digital Library. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/1469349 |
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