Optimization of Fusion Algorithm for Hybrid Pedestrian Localization and Navigation
Wang H, Bauer G, Kirsch F, Vossiek M (2012)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2012
Edited Volumes: WPNC'12 - Proceedings of the 2012 9th Workshop on Positioning, Navigation and Communication
Pages Range: 163-168
Conference Proceedings Title: 9th Workshop on Positioning, Navigation and Communication 2012 (WPNC 2012)
Event location: Dresden, Germany
DOI: 10.1109/WPNC.2012.6268758
Abstract
Hybrid pedestrian localization based on multiple data sources is becoming more and more popular. Nevertheless, accurate and reliable pedestrian localization is still a challenge due mainly to their unpredictable movement. For some applications such as interactive museum guidance unpredictable pedestrian movement is a major obstacle to accurate localization. In this paper we introduce a novel fusion algorithm using best-neighbor rating. The algorithm reduces the accumulated error originating from unreliable sensor measurements and increases the efficiency by only evaluating the nearby cells of the last estimated position. Experimental results show that a mean error of less than 1.5 M is achievable in real-world scenarios. © 2012 IEEE.
Authors with CRIS profile
Haowei Wang
Lehrstuhl für Hochfrequenztechnik
Fabian Kirsch
Lehrstuhl für Hochfrequenztechnik
Martin Vossiek
Lehrstuhl für Hochfrequenztechnik
Involved external institutions
How to cite
APA:
Wang, H., Bauer, G., Kirsch, F., & Vossiek, M. (2012). Optimization of Fusion Algorithm for Hybrid Pedestrian Localization and Navigation. In 9th Workshop on Positioning, Navigation and Communication 2012 (WPNC 2012) (pp. 163-168). Dresden, Germany, DE.
MLA:
Wang, Haowei, et al. "Optimization of Fusion Algorithm for Hybrid Pedestrian Localization and Navigation." Proceedings of the 2012 9th Workshop on Positioning, Navigation and Communication, WPNC'12, Dresden, Germany 2012. 163-168.
BibTeX: Download