TY  - JOUR
TI  - Through Wall Radar Classification of Human Micro-Doppler Using Singular Value Decomposition Analysis
EP  - 18
AV  - public
Y1  - 2016/09//
ID  - discovery1508358
N2  - The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques
PB  - MDPI AG
KW  - Science & Technology
KW  -  Physical Sciences
KW  -  Technology
KW  -  Chemistry
KW  -  Analytical
KW  -  Electrochemistry
KW  -  Instruments & Instrumentation
KW  -  Chemistry
KW  -  micro-Doppler
KW  -  FMCW radar
KW  -  through-the-wall
KW  -  classification
KW  -  SIGNATURES
KW  -  PERSONNEL
KW  -  SVD
KW  -  TRACKING
KW  -  FEATURES
KW  -  MOTIONS
VL  - 16
N1  - © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
IS  - 9
SN  - 1424-8220
UR  - http://doi.org/10.3390/s16091401
JF  - Sensors
A1  - Ritchie, M
A1  - Ash, M
A1  - Chen, Q
A1  - Chetty, K
ER  -