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http://dx.doi.org/10.7471/ikeee.2018.22.3.624

Classification of Doppler Audio Signals for Moving Target Using Hidden Markov Model in Pulse Doppler Radar  

Sim, Jae-Hun (Hanwha Systems Co., Ltd.)
Lee, Jung-Ho (LIG Nex1 Co., Ltd.)
Bae, Keun-Sung (School of Electronics Engineering, Kyungpook National University)
Publication Information
Journal of IKEEE / v.22, no.3, 2018 , pp. 624-629 More about this Journal
Abstract
Classification of moving targets in Pulse Doppler Radar(PDR) for surveillance and reconnaissance purposes is generally carried out based on listening and training experience of Doppler audio signals by radar operator. In this paper, we proposed the automatic classification method to identify the class of moving target with Doppler audio signals using the Mel Frequency Cepstral Coefficients(MFCC) and the Hidden Markov Model(HMM) algorithm which are widely used in speech recognition and the classification performance was analyzed and verified by simulations.
Keywords
Pulse Doppler Radar(PDR); Moving Target; MFCC; HMM; Automatic Classification;
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Times Cited By KSCI : 1  (Citation Analysis)
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