Polarimetric MDS of pedestrian

Radar observation and signature identification of human motions have a variety of applications in social security and rescue operations. Both simulation and real radar experiment are conducted to investigate the polarimetric micro-Doppler signatures (MDSs) of a pedestrian. In the simulation, the mot...

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Bibliographic Details
Published in:Electronics letters 2018-08, Vol.54 (17), p.1051-1053
Main Authors: Kang, Wenwu, Zhang, Yunhua, Dong, Xiao
Format: Article
Language:English
Subjects:
Carnegie Mellon University motion graphic laboratory
electromagnetic wave scattering
FEKO
HH microDoppler
human motions
Ka‐band radar experiment
MATLAB
motion estimation
motion‐captured dataset
object detection
polarimetric MDS
polarimetric microDoppler signatures
radar observation
radar polarimetry
radar scattering calculation
radar signal processing
Radar, sonar and navigation
signature identification
social rescue operation
social security operation
time‐frequency analysis
time‐frequency diagram
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Summary:Radar observation and signature identification of human motions have a variety of applications in social security and rescue operations. Both simulation and real radar experiment are conducted to investigate the polarimetric micro-Doppler signatures (MDSs) of a pedestrian. In the simulation, the motion-captured dataset developed by Carnegie Mellon University motion graphic laboratory is first used, then both Feldberechnung bei Korpern mit beliebiger Oberflache (FEKO) and MATLAB are used to calculate the radar scattering of pedestrian’ arms, based on which, horizontal-horizontal (HH) and horizontal-vertical (HV) polarimetric MDSs are analysed. Simulation results clearly show that in the time–frequency diagram, HH micro-Doppler (m-D) of arms is rising, whereas HV m-D is falling, which is verified by practical Ka-band radar experiment on a pedestrian. The work shows that by using polarimetric radar the m-D signature of human motion can be much well detected and identified which can be further explored for classification of different people.
ISSN:0013-5194
1350-911X
1350-911X
DOI:10.1049/el.2018.0208