ZTE Communications ›› 2021, Vol. 19 ›› Issue (2): 44-52.DOI: 10.12142/ZTECOM.202102006

• Special Topic • Previous Articles     Next Articles

Speed Estimation Using Commercial Wi-Fi Device in Smart Home

TIAN Zengshan, YE Chenglin(), ZHANG Gongzhui, HE Wei, JIN Yue   

  1. Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2021-03-31 Online:2021-06-25 Published:2021-07-27
  • About author:TIAN Zengshan is currently a professor of Chongqing University of Posts and Telecommunications, China. His research focuses on localization in a cellular network, personal communication, precise localization and attitude measurement with GPS, data compression, and deep learning.|YE Chenglin (s190101153@stu.cqupt.edu.cn) is currently pursuing the M. S. degree at Chongqing University of Posts and Telecommunications, China. His research interests include wireless sensing and localization.|ZHANG Gongzhui is currently pursuing the M. S. degree at Chongqing University of Posts and Telecommunications, China. His research interests include speed estimation and identity recognition.|HE Wei is an associate professor of Chongqing University of Posts and Telecommunications, China. His current research interests include wireless location, signal processing, mobile communication technology and communication software engineering.|JIN Yue is currently pursuing the Ph. D. degree at Chongqing University of Posts and Telecommunications, China. Her research interests include indoor intrusion detection and device-free tracking.
  • Supported by:
    the Science and Technology Research Project of the Chongqing Natural Science Foundation Project(CSTC2020jcyj-msxmX0842);the National Natural Science Foundation of China(61771083)

Abstract:

With the development of Internet of Things (IoT), the speed estimation technology has attracted significant attention in the field of indoor security, intelligent home and personalized service. Due to the indoor multipath propagation, the speed information is implicit in the motion-induced reflected signal. Thus, the wireless signal can be leveraged to measure the speed of moving target. Among existing speed estimation approaches, users need to either carry a specialized device or walk in a predefined route. Wi-Fi based approaches provide an alternative solution in a device-free way. In this paper, we propose a direction independent indoor speed estimation system in terms of Electromagnetic (EM) wave statistical theory. Based on the statistical characteristics of EM waves, we establish the deterministic relationship between the Autocorrelation Function (ACF) of Channel State Information (CSI) and the speed of a moving target. Extensive experiments show that the system achieves a median error of 0.18 m/s for device-free single target walking speed estimation.

Key words: CSI, speed estimation, electromagnetic wave, direction-independent, autocorrelation function