UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Aspect angle dependence and multistatic data fusion for micro-Doppler classification of armed/unarmed personnel

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. Green open access

[thumbnail of For Green Repository.pdf]
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
Downloads since deposit
209Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item