Indoor Positioning Using Nonparametric Belief Propagation Based on Spanning Trees
2010 (English)In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, 1-12 p.Article in journal (Refereed) Published
Nonparametric belief propagation (NBP) is one of the best-known methods for cooperative localization in sensor networks. It is capable of providing 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. Therefore, in this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST) created by breadth first search (BFS) method. In addition, we propose a reliable indoor model based on obtained measurements in our lab. According to our simulation results, NBP-ST performs better than NBP in terms of accuracy and communication cost in the networks with high connectivity (i.e., highly loopy networks). Furthermore, the computational and communication costs are nearly constant with respect to the transmission radius. However, the drawbacks of proposed method are a little bit higher computational cost and poor performance in low-connected networks.
Place, publisher, year, edition, pages
2010. 1-12 p.
belief propagation, spanning trees, cooperative localization, indoor positioning, breadth first search, loops
Engineering and Technology Signal Processing Communication Systems
IdentifiersURN: urn:nbn:se:liu:diva-81437DOI: 10.1155/2010/963576OAI: oai:DiVA.org:liu-81437DiVA: diva2:552464