Moving Target Localization and Activity/Gesture Recognition for Indoor Radio Frequency Sensing Applications
In this paper, a dual-frequency continuous wave radar is proposed to achieve both localization and activity/ gesture recognition simultaneously. Specifically, features of different movements will be classified by the activity and gesture recognition network (AGRNet) which is a lightweight network ba...
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| Veröffentlicht in: | IEEE sensors journal 2021-11, Vol.21 (21), p.24318-24326 |
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| container_issue | 21 |
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| container_title | IEEE sensors journal |
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| creator | Sun, Yingxiang Xiong, Haoqiu Tan, Danny Kai Pin Han, Tony Xiao Du, Rui Yang, Xun Ye, Terry Tao |
| description | In this paper, a dual-frequency continuous wave radar is proposed to achieve both localization and activity/ gesture recognition simultaneously. Specifically, features of different movements will be classified by the activity and gesture recognition network (AGRNet) which is a lightweight network based on MobileNet. The data that are recognized corresponding to walking will be used for moving target localization by comparing the phase difference in the Doppler domain between dual frequencies. In addition, a segmentation method is proposed to effectively segment continuous signals into individual time-periods corresponding to different motions by detecting the boundaries of signal changing. The experimental results show that the proposed method accomplishes the classification accuracy over 91% with 8 motion classes with a localization accuracy in the centimeter level. |
| doi_str_mv | 10.1109/JSEN.2021.3111187 |
| format | Article |
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The experimental results show that the proposed method accomplishes the classification accuracy over 91% with 8 motion classes with a localization accuracy in the centimeter level.</description><subject>Activity recognition</subject><subject>Activity/gesture recognition</subject><subject>Continuous wave radar</subject><subject>Doppler effect</subject><subject>Feature extraction</subject><subject>Feature recognition</subject><subject>Gesture recognition</subject><subject>Localization</subject><subject>Location awareness</subject><subject>micro-Doppler signature</subject><subject>Moving targets</subject><subject>Radar</subject><subject>Radio frequency</subject><subject>Segmentation</subject><subject>Sensors</subject><subject>Target recognition</subject><subject>wireless sensing</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE9PAjEQxTdGExH9AMZLE88Lnf6hu0dCADGoCWDibVO6XVLEdm0XEvz0dsE4lzfJ_ObN5CXJPeAeAM77z8vxa49gAj0KsTJxkXSA8ywFwbLLtqc4ZVR8XCc3IWwxhlxw0Uk-X9zB2A1aSb_RDZo7JXfmRzbGWSRtiYaqMQfTHPtTHZq912ihldtYcwIq59HMli7KQpbGoYnX33tt1REttQ2t77Cud0ad_MJtclXJXdB3f9pN3ifj1egpnb9NZ6PhPFUkp026BqqYVLgaCOBZxkrGgOCSaBAVyzNF4qTKOakYBxwxRXm-FkqVOQyEpJp2k8ezb-1dfCc0xdbtvY0nCxINscAYs0jBmVLeheB1VdTefEl_LAAXbaZFm2nRZlr8ZRp3Hs47Rmv9z-ecwoAQ-gtHxXOV</recordid><startdate>20211101</startdate><enddate>20211101</enddate><creator>Sun, Yingxiang</creator><creator>Xiong, Haoqiu</creator><creator>Tan, Danny Kai Pin</creator><creator>Han, Tony Xiao</creator><creator>Du, Rui</creator><creator>Yang, Xun</creator><creator>Ye, Terry Tao</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| issn | 1530-437X 1558-1748 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Activity recognition Activity/gesture recognition Continuous wave radar Doppler effect Feature extraction Feature recognition Gesture recognition Localization Location awareness micro-Doppler signature Moving targets Radar Radio frequency Segmentation Sensors Target recognition wireless sensing |
| title | Moving Target Localization and Activity/Gesture Recognition for Indoor Radio Frequency Sensing Applications |
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