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Inverting Systems of Embedded Sensors for Position Verification in Location-Aware Applications
May 2010 (vol. 21 no. 5)
pp. 722-736
ASCII Text
x 
 
Shu Chen, Yingying Chen, Wade Trappe, "Inverting Systems of Embedded Sensors for Position Verification in Location-Aware Applications," IEEE Transactions on Parallel and Distributed Systems, vol. 21, no. 5, pp. 722-736, May, 2010.
 
 
BibTex
x
 
@article{ 10.1109/TPDS.2009.110,
author = {Shu Chen and Yingying Chen and Wade Trappe},
title = {Inverting Systems of Embedded Sensors for Position Verification in Location-Aware Applications},
journal ={IEEE Transactions on Parallel and Distributed Systems},
volume = {21},
number = {5},
issn = {1045-9219},
year = {2010},
pages = {722-736},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2009.110},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Parallel and Distributed Systems
TI - Inverting Systems of Embedded Sensors for Position Verification in Location-Aware Applications
IS - 5
SN - 1045-9219
SP722
EP736
EPD - 722-736
A1 - Shu Chen,
A1 - Yingying Chen,
A1 - Wade Trappe,
PY - 2010
KW - Localization
KW - sensor networks
KW - wireless networks.
VL - 21
JA - IEEE Transactions on Parallel and Distributed Systems
ER -
 
Shu Chen, Rutgers University, North Brunswick
Yingying Chen, Stevens Institute of Technology, Castle Point on Hudson, Hoboken
Wade Trappe, Rutgers University, North Brunswick
Wireless sensor networks are typically deployed to monitor phenomena that vary over the spatial region the sensor network covers. The sensor readings may also be dual-used for additional purposes. In this paper, we propose to use the inherent spatial variability in physical phenomena, such as temperature or ambient acoustic energy, to support localization and position verification. We first present the problem of localization using general spatial information fields, and then, propose a theory for exploiting this spatial variability for localization. Our Spatial Correlation Weighting Mechanism (SCWM) uses spatial correlation across different phenomena to isolate an appropriate subset of environmental parameters for better location accuracy. We then develop an array of algorithms employing environmental parameters using a two-level approach: first, we develop the strategies on how the subset of parameters should be chosen, and second, we derive mapping functions for position estimation. Our algorithms support our theoretical model for performing localization utilizing environmental properties. Finally, we provide an experimental evaluation of our approach by using a collection of physical phenomena measured across 100 locations inside a building. Our results provide strong evidence of the viability of using general sensor readings for location-aware applications.

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Index Terms:
Localization, sensor networks, wireless networks.
Citation:
Shu Chen, Yingying Chen, Wade Trappe, "Inverting Systems of Embedded Sensors for Position Verification in Location-Aware Applications," IEEE Transactions on Parallel and Distributed Systems, vol. 21, no. 5, pp. 722-736, May 2010, doi:10.1109/TPDS.2009.110
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