Relative location estimation in wireless sensor networks Export

@article{citeulike:3157930, 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.}, author = {Patwari, N. and Hero, A. O. and Perkins, M. and Correal, N. S. and O'Dea, R. J.}, booktitle = {Signal Processing, IEEE Transactions on}, citeulike-article-id = {3157930}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/TSP.2003.814469}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1212671}, day = {15}, doi = {10.1109/TSP.2003.814469}, journal = {Signal Processing, IEEE Transactions on}, keywords = {relative-localization, sensor-networks}, month = {July}, number = {8}, pages = {2137--2148}, posted-at = {2008-08-27 09:08:41}, priority = {2}, title = {Relative location estimation in wireless sensor networks}, url = {http://dx.doi.org/10.1109/TSP.2003.814469}, volume = {51}, year = {2003} }

TY - JOUR ID - citeulike:3157930 L3 - citeulike-article-id:3157930 N2 - 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. IS - 8 JF - Signal Processing, IEEE Transactions on EP - 2148 TI - Relative location estimation in wireless sensor networks VL - 51 T2 - Signal Processing, IEEE Transactions on SP - 2137 KW - relative-localization KW - sensor-networks AU - Patwari, N AU - Hero, AO AU - Perkins, M AU - Correal, NS AU - O'Dea, RJ PY - 2003/07/15/ UR - http://dx.doi.org/10.1109/TSP.2003.814469 ER -