Indonesian Journal of Electrical Engineering and Computer Science
Vol 12, No 8: August 2014

A New Particle Filter Algorithm with Correlative Noises

Qin Lu-Fang (Xuzhou Institute of Technology)
Li Wei (Xuzhou Institute of Technology)
Sun Tao (Xuzhou Institute of Technology)
Li Jun (Xuzhou Institute of Technology)
Cao Jie (Lanzhou University of Technology)



Article Info

Publish Date
01 Aug 2014

Abstract

The standard particle filter (SPF) requirements system noise and measurement noise must be independent. In order to overcome this limit, a new kind of correlative noise particle filter (CN-PF) algorithm is proposed. In this new algorithm, system state model with correlative noise is established, and the noise related proposal distribution function characteristics were analyzed in detail. At last, the concrete form of the best proposal distribution function is derived based on the condition of the minimum variance of importance weight with the assumption of gaussian noise. Theoretical analysis and experimental results show the effectiveness of the proposed new algorithm.

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