Visible to the public MuTrack: Multiparameter Based Indoor Passive Tracking System Using Commodity WiFi

TitleMuTrack: Multiparameter Based Indoor Passive Tracking System Using Commodity WiFi
Publication TypeConference Paper
Year of Publication2020
AuthorsJin, Y., Tian, Z., Zhou, M., Wang, H.
Conference NameICC 2020 - 2020 IEEE International Conference on Communications (ICC)
Keywordsbackground clutter signals, Clutter, commodity WiFi devices, compositionality, conjugate operation, contactless awareness applications, Data Sanitization, device-free localization-tracking, DFLT system, elderly care, home security, Human Behavior, Hungarian Kalman filter, Indexes, indoor environment, indoor passive tracking system, indoor radio, Kalman filters, low-resolution parameter estimates, multi-dimensional parameters, multidimensional parameters estimator, multiparameter based indoor passive tracking system, MuTrack, parameter estimation, path components, path parameters, privacy, pubcrawl, Radar tracking, random phase errors, receiving antennas, reference antenna, reliability, reliability index, resilience, Resiliency, signal sanitization, target tracking, Tracking, weak target echoes, WiFi, WiFi signal, Wireless fidelity, wireless LAN
AbstractDevice-Free Localization and Tracking (DFLT) acts as a key component for the contactless awareness applications such as elderly care and home security. However, the random phase errors in WiFi signal and weak target echoes submerged in background clutter signals are mainly obstacles for current DFLT systems. In this paper, we propose the design and implementation of MuTrack, a multiparameter based DFLT system using commodity WiFi devices with a single link. Firstly, we select an antenna with maximum reliability index as the reference antenna for signal sanitization in which the conjugate operation removes the random phase errors. Secondly, we design a multi-dimensional parameters estimator and then refine path parameters by optimizing the complete data of path components. Finally, the Hungarian Kalman Filter based tracking method is proposed to derive accurate locations from low-resolution parameter estimates. We extensively validate the proposed system in typical indoor environment and these experimental results show that MuTrack can achieve high tracking accuracy with the mean error of 0.82 m using only a single link.
Citation Keyjin_mutrack_2020