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Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'06)
Target Classification and Pattern Recognition Using Micro-Doppler Radar Signatures
Las Vegas, Nevada
June 19-June 20
ISBN: 0-7695-2611-X
Yinan Yang, Towson University, 8000 York Road, Towson, MD
Jiajin Lei, Towson University, 8000 York Road, Towson, MD
Wenxue Zhang, Towson University, 8000 York Road, Towson, MD
Chao Lu, Towson University, 8000 York Road, Towson, MD
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.
Citation:
Yinan Yang, Jiajin Lei, Wenxue Zhang, Chao Lu, "Target Classification and Pattern Recognition Using Micro-Doppler Radar Signatures," snpd-sawn, pp.213-217, Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'06), 2006
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