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Pattern recognition based on time-frequency distributions of radar micro-Doppler dynamics

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1 Author(s)
Jiajin Lei ; Dept. of Comput. & Inf. Sci., Towson Univ., MD, USA

Radar micro-Doppler signatures are of great potential for identifying properties of unknown targets. An effective tool to extract information from the signatures is time-frequency analysis, based on which target identification and object recognition can be extended. In this paper, a method has been proposed for feature extraction and selection from simulated time-frequency distribution of micro-Doppler dynamics. Experimental results have shown that a highly discriminative feature set can be established by using this method. With this feature set, high classification performances both in training and testing stages for different classifiers have been achieved.

Published in:

Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2005 and First ACIS International Workshop on Self-Assembling Wireless Networks. SNPD/SAWN 2005. Sixth International Conference on

Date of Conference:

23-25 May 2005

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