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

Francesco Fioranelli; Matthew Ritchie; Hugh Griffiths

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

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Author(s): Francesco Fioranelli ¹ ; Matthew Ritchie ¹ ; Hugh Griffiths ¹
- Affiliations: 1: Electronic & Electrical Engineering, University College London, London, UK
Source: Volume 9, Issue 9, December 2015, p. 1231 – 1239
DOI: 10.1049/iet-rsn.2015.0058 , Print ISSN 1751-8784, Online ISSN 1751-8792

Received 30/01/2015, Accepted 26/06/2015, Revised 22/06/2015, Published 01/12/2015

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.

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

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