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Sensors 2017, 17(12), 2769; https://doi.org/10.3390/s17122769

An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification

1
Department of Mathematics and Computer Science, Changsha University, Changsha 410022, China
2
School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
*
Author to whom correspondence should be addressed.
Received: 19 October 2017 / Revised: 20 November 2017 / Accepted: 27 November 2017 / Published: 29 November 2017
(This article belongs to the Section Physical Sensors)
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Abstract

In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference. View Full-Text
Keywords: micro-doppler signal; radar; activity classification; time-frequency analysis; support vector machine (SVM) micro-doppler signal; radar; activity classification; time-frequency analysis; support vector machine (SVM)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Li, F.; Yang, C.; Xia, Y.; Ma, X.; Zhang, T.; Zhou, Z. An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification. Sensors 2017, 17, 2769.

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