DMCA
1A Fade Level-based Spatial Model for Radio Tomographic Imaging
| Citations: | 6 - 5 self |
BibTeX
@MISC{Kaltiokallio_1afade,
author = {Ossi Kaltiokallio and Maurizio Bocca and Neal Patwari Member},
title = {1A Fade Level-based Spatial Model for Radio Tomographic Imaging},
year = {}
}
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Abstract
Abstract—RSS-based device-free localization (DFL) monitors changes in the received signal strength (RSS) measured by a network of static wireless nodes to locate and track 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 spatial weight model that is a function of the fade level, i.e., a measure of whether a link is experiencing destructive or constructive multipath interference, and of the sign of RSS change. In addition, a measurement model is proposed which calculates for each RSS measurement the probability of a person being located inside the derived spatial impact area. An online radio tomographic imaging (RTI) 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 performance of the proposed 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. Index Terms—wireless sensor networks, device-free localiza-tion, radio tomographic imaging, indoor localization I.
Keyphrases
radio tomographic imaging fade level-based spatial model spatial impact area link r high accuracy measurement model received signal strength sensor network presented model typical one-bedroom apartment constructive multipath interference open indoor environment fade level new system extensive experiment model parameter index term derived spatial impact area electronic device r change spatial weight model monitor change static wireless node through-wall scenario device-free localiza-tion current model indoor localization online radio tomographic imaging constant size channel diversity abstract rss-based device-free localization
