Personnel recognition based on multistatic micro-Doppler and singular value decomposition features

被引:14
作者
Fioranelli, F. [1 ]
Ritchie, M. [1 ]
Griffiths, H. [1 ]
机构
[1] UCL, Dept Elect & Elect Engn, London, England
关键词
CLASSIFICATION; RADAR;
D O I
10.1049/el.2015.3513
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The use of micro-Doppler signatures experimentally collected by a multistatic radar system to recognise and classify different people walking is discussed. A suitable feature based on singular value decomposition of the spectrograms is proposed and tested with different types of classifiers. It is shown that high accuracy of between 97 and 99% can be achieved when multistatic data are used to perform the classification.
引用
收藏
页码:2144 / 2145
页数:2
相关论文
共 10 条
[1]  
Chen V. C., 2014, Radar-Micro Doppler Signatures: Processing and Applications
[2]  
de Wit JJM, 2014, 2014 INTERNATIONAL RADAR CONFERENCE (RADAR)
[3]   Determining human target facing orientation using bistatic radar micro-Doppler signals [J].
Fairchild, Dustin P. ;
Narayanan, Ram M. .
ACTIVE AND PASSIVE SIGNATURES V, 2014, 9082
[4]   Classification of Unarmed/Armed Personnel Using the NetRAD Multistatic Radar for Micro-Doppler and Singular Value Decomposition Features [J].
Fioranelli, Francesco ;
Ritchie, Matthew ;
Griffiths, Hugh .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2015, 12 (09) :1933-1937
[5]   Multistatic human micro-Doppler classification of armed/unarmed personnel [J].
Fioranelli, Francesco ;
Ritchie, Matthew ;
Griffiths, Hugh .
IET RADAR SONAR AND NAVIGATION, 2015, 9 (07) :857-865
[6]   Human Detection Using Doppler Radar Based on Physical Characteristics of Targets [J].
Kim, Youngwook ;
Ha, Sungjae ;
Kwon, Jihoon .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2015, 12 (02) :289-293
[7]   Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine [J].
Kim, Youngwook ;
Ling, Hao .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2009, 47 (05) :1328-1337
[8]   A new approach for classification of human gait based on time-frequency feature representations [J].
Orovic, Irena ;
Stankovic, Srdjan ;
Amin, Moeness .
SIGNAL PROCESSING, 2011, 91 (06) :1448-1456
[9]  
Ricci R., IET RADAR S IN PRESS
[10]  
Trevor Hastie R.T.J.F., 2009, The elements of statistical learning: data mining, inference, and prediction, V2