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http://dx.doi.org/10.7471/ikeee.2020.24.3.783

Design and Implementation of Human-Detecting Radar System for Indoor Security Applications  

Jang, Daeho (School of Electronics and Information Engineering, Korea Aerospace University)
Kim, Hyeon (School of Electronics and Information Engineering, Korea Aerospace University)
Jung, Yunho (School of Electronics and Information Engineering, Korea Aerospace University)
Publication Information
Journal of IKEEE / v.24, no.3, 2020 , pp. 783-790 More about this Journal
Abstract
In this paper, the human detecting radar system for indoor security applications is proposed, and its FPGA-based implementation results are presented. In order to minimize the complexity and memory requirements of the computation, the top half of the spectrogram was used to extract features, excluding the feature extraction techniques that require complex computation, feature extraction techniques were proposed considering classification performance and complexity. In addition, memory requirements were minimized by designing a pipeline structure without storing the entire spectrogram. Experiments on human, dog and robot cleaners were conducted for classification, and 96.2% accuracy performance was confirmed. The proposed system was implemented using Verilog-HDL, and we confirmed that a low-area design using 1140 logics and 6.5 Kb of memory was possible.
Keywords
radar target classification; SVM; feature extraction; human detecting;
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Times Cited By KSCI : 6  (Citation Analysis)
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