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Safe Fusion Compared to Established Distributed Fusion Methods
Swedish Defence Research Agency (FOI).
Swedish Defence Research Agency (FOI).
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-1971-4295
2016 (English)In: Proceedings of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2016Conference paper (Refereed)
Abstract [en]

The safe fusion algorithm is benchmarked againstthree other methods in distributed target tracking scenarios. Safefusion is a fairly unknown method similarly to, e.g., covarianceintersection, that can be used to fuse potentially dependentestimates without double counting data. This makes it suitablefor distributed target tracking, where dependencies are oftenunknown or difficult to derive. The results show that safe fusionis a very competitive alternative in five evaluated scenarios, whileat the same time easy to implement and compute compared tothe other evaluated methods. Hence, safe fusion is an attractivealternative in track to track fusion systems.

Place, publisher, year, edition, pages
2016.
Keyword [en]
Distributed Methods; Localization, Tracking and Navigation; Multi-Robot Systems and Mobile Sensor Networks
National Category
Control Engineering Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-131425OAI: oai:DiVA.org:liu-131425DiVA: diva2:972030
Conference
IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Baden-Baden, Germany, 19-21 September, 2016
Projects
Scalable Kalman Filters
Funder
Swedish Research Council
Available from: 2016-09-20 Created: 2016-09-20 Last updated: 2016-09-20

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Hendeby, Gustaf
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ReferencesLink to record
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