Target Classification and Pattern Recognition Using Micro-Doppler Radar Signatures

Authors:
Yinan Yang;Jiajin Lei;Wenxue Zhang;Chao Lu
Affiliations:
Towson University, 8000 York Road, Towson, MD;Towson University, 8000 York Road, Towson, MD;Towson University, 8000 York Road, Towson, MD;Towson University, 8000 York Road, Towson, MD
Venue:
SNPD-SAWN '06 Proceedings of the Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Year:
2006

Citing 0
Cited 3

Human identifications using micro-Doppler signatures

ARP '08 Proceedings of the Fifth IASTED International Conference on Antennas, Radar and Wave Propagation
Radar micro-Doppler for long range front-view gait recognition

BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Radar measurement of human polarimetric micro-doppler

Journal of Electrical and Computer Engineering - Special issue on Advances in Radar Technologies

Quantified Score

Hi-index	0.00

Visualization

Abstract

Micro-motions, such as vibrations or rotations of an object or structures on the object, induce additional frequency modulations on returned radar signal, which generates sidebands about the object's Doppler frequency, called micro-Doppler [1,2,4]. In this paper, we investigated statistical classification methods for target classification using their micro-Doppler signatures. At this stage only simulated data are studied, and two models are used to generate simulation data: point scatter model and RCS model. Both models are tested and compared for their performance on target classification.