A distributed information fusion method for localization based on Pareto optimization
2011 (English)In: 7th IEEE International Conference on Distributed Computing in Sensor Systems(DCOSS), 2011Conference paper (Refereed)
To overcome the limitations of specific positioning techniques for mobile wireless nodes and achieve a high accuracy, the fusion of heterogeneous sensor information is an appealing strategy. In this paper, the problem of optimal fusion of ranging information typically provided by Ultra-Wideband radio with speed and absolute orientation information is addressed. A new distributed recursive estimation method is proposed. The method does not assume any motion model of mobile nodes and is based on a Pareto optimization. The challenging part of the new estimator is the characterization of the statistical information needed to model the optimization problem. The proposed estimator is validated by Monte Carlo simulations, and the performance is compared to several Kalman-based filters commonly employed for localization and sensor fusion. Much better performance is achieved, but at the price of an increased computational complexity.
Place, publisher, year, edition, pages
IdentifiersURN: urn:nbn:se:kth:diva-46336DOI: 10.1109/DCOSS.2011.5982155ISI: 000299427700019ScopusID: 2-s2.0-80052469881ISBN: 978-145770513-7OAI: oai:DiVA.org:kth-46336DiVA: diva2:453674
7th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS'11. Barcelona. 27 June 2011 through 29 June 2011
FunderTrenOp, Transport Research Environment with Novel PerspectivesICT - The Next Generation
QC 201111072011-11-032011-11-032012-04-03Bibliographically approved