An Improved Unscented Particle Filter with Global Sampling Strategy. (9th December 2014)

• Record Type: Journal Article
• Authors: Zhao, Yi-zheng
• Other Names: Dong Hongli Academic Editor.
• Is Part Of: Journal of computational engineering. Volume 2014(2014)
• Publication Date: 2014-12-09
• Subjects: Engineering mathematics -- Periodicals; Engineering -- Mathematical models -- Periodicals; Engineering -- Mathematical models; Engineering mathematics; Periodicals; 620.00285
• DOI: 10.1155/2014/175820
• Languages: English
• ISSNs: 2356-7260

Abstract

Abstract : Particle filter (PF) has many variations and one of the most popular is the unscented particle filter (UPF). UPF uses the unscented Kalman filter (UKF) to generate particles in the PF framework and has a better performance than the standard PF. However, UPF suffers from its high computation complexity because it has to execute UKF to each particle to obtain proposal distribution. This paper gives an improved UPF aiming at reducing the computation complexity of the algorithm. In comparison to the standard UPF, the new strategy generates proposal distribution from the mean and covariance value of the whole particles instead of from each particle. Thus the improved algorithm utilizes the characteristics of the whole particles and only needs to perform UKF algorithm once to get the proposal distribution at each time step. Experimental results show that, compared to standard UPF, the improved algorithm reduces the time consumption greatly almost without performance degradation.