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Nonparametric Belief Propagation Based on Spanning Trees for Cooperative Localization in Wireless Sensor Networks

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2 Author(s)
Savic, V. ; Signal Process. Applic. Group, Polytech. Univ. of Madrid, Madrid, Spain ; Zazo, S.

Nonparametric belief propagation (NBP) is one of the best-known methods for cooperative localization in sensor networks. It is capable to provide information about location estimation with appropriate uncertainty and to accommodate non-Gaussian distance measurement errors. However, the accuracy of NBP is questionable in loopy networks. In this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST) created by breadth first search (BFS) method. According to our simulation results, NBP-ST performs better than NBP in terms of accuracy, computational and communication cost in the networks with high connectivity (i.e., highly loopy networks).

Published in:

Vehicular Technology Conference Fall (VTC 2010-Fall), 2010 IEEE 72nd

Date of Conference:

6-9 Sept. 2010