Performance analysis of centroid and SVD features for personnel recognition using multistatic micro-Doppler

Fioranelli, F. , Ritchie, M. and Griffiths, H. (2016) Performance analysis of centroid and SVD features for personnel recognition using multistatic micro-Doppler. IEEE Geoscience and Remote Sensing Letters, 13(5), pp. 725-729. (doi: 10.1109/LGRS.2016.2539386)

Abstract

In this letter, we investigate the use of micro-Doppler signatures experimentally recorded by a multistatic radar system to perform recognition of people walking. Three different sets of features are tested, taking into account the impact on the overall classification performance of parameters, such as aspect angle, types of classifier, different values of signal-to-noise ratio, and different ways of exploiting multistatic information. High classification accuracy of above 98% is reported for the most favorable aspect angle, and the benefit of using multistatic data at less favorable angles is discussed.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Fioranelli, Dr Francesco
• Authors: Fioranelli, F., Ritchie, M., and Griffiths, H.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: IEEE Geoscience and Remote Sensing Letters
• Publisher: IEEE
• ISSN: 1545-598X
• ISSN (Online): 1558-0571
• Published Online: 30 March 2016
• Copyright Holders: Copyright © 2016 IEEE
• First Published: First published in IEEE Geoscience and Remote Sensing Letters 13(5): 725-729
• Publisher Policy: Reproduced in accordance with the publisher copyright policy