Radar micro-Doppler based human activity classification for indoor and outdoor environments

Matthew Zenaldin, Ram M. Narayanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations

Abstract

This paper presents the results of our experimental investigation into how different environments impact the classification of human motion using radar micro-Doppler (MD) signatures. The environments studied include free space, through-thewall, leaf tree foliage, and needle tree foliage. Results on presented on classification of the following three motions: crawling, walking, and jogging. The classification task was designed how to best separate these movements. The human motion data were acquired using a monostatic coherent Doppler radar operating in the C-band at 6.5 GHz from a total of six human subjects. The received signals were analyzed in the time-frequency domain using the Short-time Fourier Transform (STFT) which was used for feature extraction. Classification was performed using a Support Vector Machine (SVM) using a Radial Basis Function (RBF). Classification accuracies in the range 80-90% were achieved to separate the three movements mentioned.

Original languageEnglish (US)
Title of host publicationRadar Sensor Technology XX
EditorsArmin Doerry, Kenneth I. Ranney
PublisherSPIE
ISBN (Electronic)9781510600706
DOIs
StatePublished - 2016
EventRadar Sensor Technology XX - Baltimore, United States
Duration: Apr 18 2016Apr 21 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9829
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

OtherRadar Sensor Technology XX
Country/TerritoryUnited States
CityBaltimore
Period4/18/164/21/16

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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