A Particle Filter Algorithm Based on Mixing of Prior Probability Density and UKF as Generate Importance Function

Liu Lu; J. Wang; M. Yang; S. Geng

doi:10.4028/www.scientific.net/AMM.743.403

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 743A Particle Filter Algorithm Based on Mixing of...

A Particle Filter Algorithm Based on Mixing of Prior Probability Density and UKF as Generate Importance Function

Abstract:

As an important nonlinear filter theory, particle filter is a heated issue in domestic and foreign researches. The option of importance density is one of the key steps of particle filter algorithm. The proper option of importance density can minish the negative influence of filter algorithm caused by degeneracy problem. This paper introduces several widely-used options of importance density systemically, and analyzes their features and applied perspectives respectively. The paper also advances a comprehensive method of importance density, analyzes its technical features, explores the adjudgement and improvement of this method based on various performance, and finally puts forward the necessary further study according to the engineer requirements.

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Periodical:

Applied Mechanics and Materials (Volume 743)

Pages:

403-406

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.743.403

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Online since:

March 2015

Authors:

Liu Lu*, J. Wang, M. Yang, S. Geng

Keywords:

Importance Function, Particle Filter, Proposal Distribution, SIS

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* - Corresponding Author

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