Bayes optimal knowledge exploitation for target tracking with hard constraints
dc.contributor.author | Papi, Francesco | |
dc.contributor.author | Podt, M. | |
dc.contributor.author | Boers, Y. | |
dc.contributor.author | Battistello, G. | |
dc.contributor.author | Ulmke, M. | |
dc.date.accessioned | 2017-01-30T12:44:50Z | |
dc.date.available | 2017-01-30T12:44:50Z | |
dc.date.created | 2015-10-29T04:09:49Z | |
dc.date.issued | 2012 | |
dc.identifier.citation | Papi, F. and Podt, M. and Boers, Y. and Battistello, G. and Ulmke, M. 2012. Bayes optimal knowledge exploitation for target tracking with hard constraints, in Proceedings of the 9th IET Data Fusion & Target Tracking Conference 2012: Algorithms & Applications, May 16-17 2012, pp. 1-6. London: The Institution of Engineering and Technology. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/24744 | |
dc.identifier.doi | 10.1049/cp.2012.0411 | |
dc.description.abstract |
Nonlinear target tracking is a well known problem and its Bayes optimal solution, based on particle filtering techniques, is nowadays applied in high performance surveillance systems. Oftentimes, additional information about the environment and the target is available, and can be formalized in terms of constraints on target dynamics. Hence, a Constrained version of the Bayesian Filtering problem has to be solved to achieve optimal tracking performance. In this paper we consider the Constrained Filtering problem for the case of perfectly known hard constraints. We clarify that in such a case the Particle Filter (PF) is still Bayes optimal if we can correctly model the constraints. We then show that from a Bayesian viewpoint, exploitation of the available knowledge in the prediction or in the update step are equivalent. Finally, we consider simple techniques to exploit constraints in the prediction and update steps of a PF, and use the Kullback-Leibler divergence to illustrate their equivalence through simulations. | |
dc.title | Bayes optimal knowledge exploitation for target tracking with hard constraints | |
dc.type | Conference Paper | |
dcterms.source.volume | 2012 | |
dcterms.source.number | 595 CP | |
dcterms.source.startPage | 11 | |
dcterms.source.endPage | 11 | |
dcterms.source.title | IET Conference Publications | |
dcterms.source.series | IET Conference Publications | |
dcterms.source.isbn | 9781849196246 | |
curtin.department | Department of Electrical and Computer Engineering | |
curtin.accessStatus | Fulltext not available |