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.
%0 Journal Article
%1 1212671
%A Patwari, N.
%A Hero, A. O.
%A Perkins, M.
%A Correal, N. S.
%A O'Dea, R. J.
%D 2003
%J IEEE Transactions on Signal Processing
%K location_estimation ml4pos
%N 8
%P 2137-2148
%R 10.1109/TSP.2003.814469
%T Relative location estimation in wireless sensor networks
%U http://ieeexplore.ieee.org/abstract/document/1212671/
%V 51
%X 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.
@article{1212671,
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.},
added-at = {2017-07-21T14:15:23.000+0200},
author = {Patwari, N. and Hero, A. O. and Perkins, M. and Correal, N. S. and O'Dea, R. J.},
biburl = {https://www.bibsonomy.org/bibtex/297058398dd5636b2966cd6558d47e43c/alexgrimm94},
description = {Relative location estimation in wireless sensor networks - IEEE Xplore Document},
doi = {10.1109/TSP.2003.814469},
interhash = {b490d8378ecf89fdf668294946798ca2},
intrahash = {97058398dd5636b2966cd6558d47e43c},
issn = {1053-587X},
journal = {IEEE Transactions on Signal Processing},
keywords = {location_estimation ml4pos},
month = aug,
number = 8,
pages = {2137-2148},
timestamp = {2017-07-21T14:15:23.000+0200},
title = {Relative location estimation in wireless sensor networks},
url = {http://ieeexplore.ieee.org/abstract/document/1212671/},
volume = 51,
year = 2003
}