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An auxiliary particle filtering algorithm with inequality constraints
journal contributionposted on 2016-11-11, 14:25 authored by Baibing LiBaibing Li, Cunjia LiuCunjia Liu, Wen-Hua ChenWen-Hua Chen
For nonlinear non-Gaussian stochastic dynamic systems with inequality state constraints, this paper presents an efficient particle filtering algorithm, constrained auxiliary particle filtering algorithm. To deal with the state constraints, the proposed algorithm probabilistically selects particles such that those particles far away from the feasible area are less likely to propagate into the next time step. To improve on the sampling efficiency in the presence of inequality constraints, it uses a highly effective method to perform a series of constrained optimization so that the importance distributions are constructed efficiently based on the state constraints. The caused approximation errors are corrected using the importance sampling method. This ensures that the obtained particles constitute a representative sample of the true posterior distribution. A simulation study on vehicle tracking is used to illustrate the proposed approach.
This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) Autonomous and Intelligent Systems programme (grant number EP/J011525/1) with BAE Systems as the leading industrial partner.
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Published inIEEE Transactions on Automatic Control
CitationLI, B., LIU, C. and CHEN, W-H., 2017. An auxiliary particle filtering algorithm with inequality constraints. IEEE Transactions on Automatic Control, 62 (9), pp. 4639-4646.
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Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/
NotesThis is an Open Access Article. It is published by IEEE under the creative Commons Attribution 3.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/