2013/02/24 by Ossi Kaltiokallio, Kaltiokallio, Ossi, Maurizio Bocca +3 · 16 citations
Computer Science · Engineering · Social Sciences · #Cartography #Computer science #Data Management and Algorithms #Environmental science #FOS: Computer and information sciences #Geographic Information Systems Studies #Geography #Human-Computer Interaction (cs.HC) #Indoor and Outdoor Localization Technologies #Networking and Internet Architecture (cs.NI) #RSS #Remote sensing #Scale (ratio) #World Wide Web #cs.HC #cs.NI
paper · pdf · doi:10.48550/arxiv.1302.5914
published in arXiv (Cornell University) (Cornell University) · 13 pages
arxiv created 2013/02/24 · openalex publication_date 2013/02/24 · arxiv updated 2013/02/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
RSS-based device-free localization (DFL) monitors changes in the received signal strength (RSS) measured by a network of static wireless nodes to locate people without requiring them to carry or wear any electronic device. Current models assume that the spatial impact area, i.e., the area in which a person affects a link's RSS, has constant size. This paper shows that the spatial impact area varies considerably for each link. Data from extensive experiments are used to derive a multi-scale spatial weight model that is a function of the fade level, i.e., the difference between the predicted and measured RSS, and of the direction of RSS change. In addition, a measurement model is proposed which gives a probability of a person locating inside the derived spatial model for each given RSS measurement. A real-time radio tomographic imaging system is described which uses channel diversity and the presented models. Experiments in an open indoor environment, in a typical one-bedroom apartment and in a through-wall scenario are conducted to determine the accuracy of the system. We demonstrate that the new system is capable of localizing and tracking a person with high accuracy (<0.30 m) in all the environments, without the need to change the model parameters.