DocumentCode :
1243144
Title :
Relative location estimation in wireless sensor networks
Author :
Patwari, Neal ; Hero, Alfred O., III ; Perkins, Matt ; Correal, Neiyer S. ; O´Dea, Robert J.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA
Volume :
51
Issue :
8
fYear :
2003
Firstpage :
2137
Lastpage :
2148
Abstract :
Self-configuration in wireless sensor networks is a general class of estimation problems that we study via the Cramer-Rao bound (CRB). Specifically, we consider sensor location estimation when sensors measure received signal strength (RSS) or time-of-arrival (TOA) between themselves and neighboring sensors. A small fraction of sensors in the network have a known location, whereas the remaining locations must be estimated. We derive CRBs and maximum-likelihood estimators (MLEs) under Gaussian and log-normal models for the TOA and RSS measurements, respectively. An extensive TOA and RSS measurement campaign in an indoor office area illustrates MLE performance. Finally, relative location estimation algorithms are implemented in a wireless sensor network testbed and deployed in indoor and outdoor environments. The measurements and testbed experiments demonstrate 1-m RMS location errors using TOA, and 1- to 2-m RMS location errors using RSS.
Keywords :
Gaussian distribution; channel estimation; direction-of-arrival estimation; indoor radio; log normal distribution; sensor fusion; signal detection; Cramer-Rao bound; Gaussian models; indoor environments; indoor office area; log-normal models; outdoor environments; radio channel measurement; received signal strength; relative location estimation; self-configuration; sensor location estimation; time-of-arrival; wireless sensor networks; Area measurement; Costs; Intelligent networks; Maximum likelihood estimation; Monitoring; Position measurement; Protocols; Signal processing algorithms; Testing; Wireless sensor networks;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2003.814469
Filename :
1212671
Link To Document :
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