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Mobile tracking in unknown non-line-of-sight conditions

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientific


Original languageEnglish
Title of host publicationProceedings of the International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Service UPINLBS 2010, October 14-15, 2010, Kirkkonummi, Finland
Place of PublicationHelsinki
Number of pages4
Publication statusPublished - 2010
Publication typeB3 Non-refereed article in conference proceedings


This paper studies the mobile tracking problem in mixed line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, where the statistics of NLOS error are assumed unknown. Three different models are used to describe the NLOS errors. A Rao-Blackwellized particle filtering with parameter learning (RBPF-PL) is presented, in which the posterior of sight conditions is estimated by particle filtering while the mobile state and NLOS parameters are analytically computed. Simulation results are provided to evaluate the performance of RBPF-PL variants in different situations. Simulation show that unless it is known that NLOS noise has the same bias and variance in all the observations, the more complicated models should be employed as they work correctly even in NLOS model mismatch, with only slightly more computational complexity.

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Field of science, Statistics Finland

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