Multi-target out-of-sequence data association

Maskell, S. R., Everitt, R. G., Wright, R. and Briers, M. (2004) Multi-target out-of-sequence data association. In: Proceedings of the Seventh International Conference on Information Fusion.

Abstract/Summary

In data fusion systems, one often encounters measurements of past target locations and then wishes to deduce where the targets are currently located. Recent research on the processing of such out-of-sequence data has culminated in the development of a number of algorithms for solving the associated tracking problem. This paper reviews these different approaches in a common Bayesian framework and proposes an architecture that orthogonalises the data association and out-of-sequence problems such that any combination of solutions to these two problems can be used together. The emphasis is not on advocating one approach over another on the basis of computational expense, but rather on understanding the relationships between the algorithms so that any approximations made are explicit.

Item Type	Conference or Workshop Item (Paper)
URI	https://reading-clone.eprints-hosting.org/id/eprint/29122
Refereed	Yes
Divisions	No Reading authors. Back catalogue items Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Applied Statistics
Uncontrolled Keywords	data,data association,it should be acknowledged,kalman filter,out-of-,out-of-sequence data more efficiently,particle filter,sensor fusion,sequence measurements,simply reprocesses all the,than an algorithm that,tracking
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