Unscented Particle Double Layer Filter
2018 21ST INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION)(2018)
摘要
The Particle filter (PF) provides a general numerical tool to deal with the non-Gaussian filtering problems, but it has the particle depletion problem and so on. The unscented particle filter (UPF) can solve the problem of particle depletion, but it has the computationally intensive problem and so on. To overcome these problems, the unscented particle double layer filter (UPDLF) is proposed. The proposed algorithm uses the PF algorithm to replace the state transition density function in the UKF algorithm, and updates the weights of each deterministic sampling point based on the new measurements. Finally, the state estimation at each time is obtained. The numerical simulation with two examples shows that the proposed filter outperforms the PF algorithm and the UPF algorithm.
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关键词
state estimation, sampling strategy, particle filter, unscented particle filter
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