Journal Article10.1049/IP-RSN:20030741
Interacting multiple model particle filter
Yvo Boers,J.N. Driessen +1 more
- 03 Dec 2003
- Vol. 150, Iss: 5, pp 344-349
257
TL;DR: In this article, a new method for multiple model particle filtering for Markovian switching systems is presented, which is a combination of the interacting multiple model (IMM) filter and a (regularised) particle filter.
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Abstract: A new method for multiple model particle filtering for Markovian switching systems is presented. This new method is a combination of the interacting multiple model (IMM) filter and a (regularised) particle filter. The mixing and interaction is similar to that in a conventional IMM filter. However, in every mode a regularised particle filter is running. The regularised particle filter probability density is a mixture of Gaussian probability densities. The proposed method is able to deal with nonlinearities and non-Gaussian noise. Furthermore, the new method keeps a fixed number of particles in each mode, and therefore it does not suffer from the potential drawbacks of existing multiple model particle filters for Markovian switching systems.
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Citations
Particle filtering for positioning and tracking applications
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Efficient particle filter for jump Markov nonlinear systems
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