Fioranelli, F;
Ritchie, M;
Griffiths, H;
(2015)
Aspect angle dependence and multistatic data fusion for micro-Doppler classification of armed/unarmed personnel.
IET Radar, Sonar and Navigation
, 9
(9)
pp. 1231-1239.
10.1049/iet-rsn.2015.0058.
Preview |
Text
For Green Repository.pdf Download (810kB) | Preview |
Abstract
This study discusses the analysis of multistatic micro-Doppler signatures and related features to distinguish and classify unarmed and potentially armed personnel. The application of radar systems to distinguish different motion types has been previously proposed and this work aims to further investigate the applicability of this in more scenarios. Real data have been collected using a multistatic radar system in a series of experiments involving several individuals performing different movements. Changes in classification accuracy as a function of different aspect angle between the direction in which the target faces and the line-of-sight of the radar nodes are analysed. Multiple data fusion methodologies are proposed, showing that significant improvement of the classification accuracy can be achieved when using separate classification at each node followed by a voting procedure to reach the final decision. This is beneficial especially at those aspect angles for which micro-Doppler detection is less favourable.
| Type: | Article |
|---|---|
| Title: | Aspect angle dependence and multistatic data fusion for micro-Doppler classification of armed/unarmed personnel |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1049/iet-rsn.2015.0058 |
| Publisher version: | http://dx.doi.org/10.1049/iet-rsn.2015.0058 |
| Language: | English |
| Additional information: | This paper is a postprint of a paper submitted to and accepted for publication in IET Radar, Sonar & Navigation and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library |
| Keywords: | Signal classification, Doppler radar, radar detection, sensor fusion |
| 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/1471508 |
Archive Staff Only
 |
View Item |
