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- W2070036321 abstract "The particle filter is widely employed for estimation of non-Gaussian problems. A disadvantage of the particle filter is long computation time when a large number of particles is used. In this paper, distributed Rao-Blackwellized particle filter is explored in order to produce a common estimate by distributing the particles in several agents. By implementing a consensus algorithm of the estimated global statistics it is shown that, in each agent, the estimated global statistics is more accurate than the local, per-agent statistics. For verification, the numerical example of a vertical channel of an inertial navigation system with barometric altimeter aiding is given, which confirms that DRBPF reduces errors effectively." @default.
- W2070036321 created "2016-06-24" @default.
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- W2070036321 date "2014-06-01" @default.
- W2070036321 modified "2023-09-27" @default.
- W2070036321 title "Jump-Markov process estimation based on distributed Rao-Blackwellized particle filter" @default.
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- W2070036321 doi "https://doi.org/10.1109/icca.2014.6871050" @default.
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