Rao-Blackwellised unscented particle filtering for jump Markov non-linear systems: an H ∞ approach
Rao-Blackwellised unscented particle filtering for jump Markov non-linear systems: an H ∞ approach
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DOI：
10.1049/iet-spr.2009.0306
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发表时间：
2011-04
影响因子：
1.7
通讯作者：
Wenling Li;Y. Jia
中科院分区：
文献类型：
--
作者：
Wenling Li;Y. Jia
针对具有未知噪声统计的跳变马尔可夫非线性系统，提出了一种稳健的Rao-Blackwell粒子滤波算法。在H-∞环境下，应用无迹变换技术，提出了一种非线性滤波器，用于更新径向基函数框架中的连续状态粒子。此外，还提出了一种根据性能要求自适应调整扰动容限的方法。文中还给出了采用该方法的仿真结果。
In this study, a robust Rao-Blackwellised particle filter (RBPF) is proposed for jump Markov non-linear systems (JMNLSs) with unknown noise statistics. A non-linear filter is presented by applying the unscented transform technique in the H∞ setting, which is used to update the continuous-state particles in the RBPF framework. Moreover, a way to adaptively adjust the disturbance tolerance level for performance requirement is presented. Simulation results using the proposed approach are also presented.