TY  - JOUR
KW  - Science & Technology
KW  -  Technology
KW  -  Engineering
KW  -  Electrical & Electronic
KW  -  Telecommunications
KW  -  Engineering
KW  -  RADAR
KW  -  SIGNATURES
KW  -  DESIGN
ID  - discovery1533714
N2  - This study analyses the use of human micro-Doppler signatures collected using a multistatic radar system to identify and classify unarmed and potentially armed personnel walking within a surveillance area. The signatures were recorded in a series of experimental tests and analysed through short time Fourier transform followed by feature extraction and classification. Features based on singular value decomposition and on the centroid of the micro-Doppler signature are proposed and their suitability for armed versus unarmed classification purposes discussed. It is shown that classification accuracy above 95% can be achieved using a single feature. Features based on the centroid of the signatures are shown to be also effective in cases where there are two people walking together in the same direction and at similar speed, and one of them may be armed or not, i.e. for targets not easily separable in range or in Doppler.
PB  - INST ENGINEERING TECHNOLOGY-IET
TI  - Centroid features for classification of armed/unarmed multiple personnel using multistatic human micro-Doppler
EP  - 1710
AV  - public
Y1  - 2016/04/27/
JF  - IET Radar, Sonar & Navigation
A1  - Fioranelli, F
A1  - Ritchie, M
A1  - Griffiths, H
SN  - 1751-8792
UR  - http://doi.org/10.1049/iet-rsn.2015.0493
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
IS  - 9
VL  - 10
SP  - 1702
ER  -