An Experimental Study of RSS-Based Indoor Localization Using Nonparametric Belief Propagation Based on Spanning Trees
2010 (English)In: Proc. of Intl. Conf. on Sensor Technologies and Applications, 2010, 238-243 p.Conference paper, Presentation (Refereed)
Nonparametric belief propagation (NBP) is the well-known method for cooperative localization in wireless 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. 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 received-signal-strength (RSS) measurements in our lab. According to our experimental 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).
Place, publisher, year, edition, pages
2010. 238-243 p.
indoor localization, breadth first search, nonparametric belief propagation, sensor networks, spanning tree
Engineering and Technology Signal Processing Communication Systems
IdentifiersURN: urn:nbn:se:liu:diva-81370DOI: 10.1109/SENSORCOMM.2010.44ISBN: 978-1-4244-7538-4OAI: oai:DiVA.org:liu-81370DiVA: diva2:552072
Intl. Conf. on Sensor Technologies and Applications, Venice, Italy