@inbook {19602,
	title = {Algorithms for Location Estimation Based on RSSI Sampling},
	booktitle = {Algorithmic Aspects of Wireless Sensor Networks},
	series = {Lecture Notes in Computer Science},
	year = {2008},
	month = {2008/01/01/},
	pages = {72 - 86},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	abstract = {In this paper, we re-examine the RSSI measurement model for location estimation and provide the first detailed formulation of the probability distribution of the position of a sensor node. We also show how to use this probabilistic model to efficiently compute a good estimation of the position of the sensor node by sampling multiple readings from the beacons (where we do not merely use the mean of the samples) and then minimizing a function with an acceptable computational effort. The results of the simulation of our method in TOSSIM indicate that the location of the sensor node can be computed in a small amount of time and that the quality of the solution is competitive with previous approaches.},
	keywords = {Algorithm Analysis and Problem Complexity, Computer Communication Networks, Data structures, Discrete Mathematics in Computer Science, Information Systems and Communication Service},
	isbn = {978-3-540-92861-4, 978-3-540-92862-1},
	url = {http://link.springer.com/chapter/10.1007/978-3-540-92862-1_7},
	author = {Charalampos Papamanthou and Preparata, Franco P. and Tamassia, Roberto},
	editor = {Fekete, S{\'a}ndor P.}
}
