Particle filter based on one‐step smoothing with adaptive iteration. Issue 5 (1st July 2017)

• Record Type: Journal Article
• Authors: Yan, Zhibin; Yuan, Yanhua
• Is Part Of: IET signal processing. Volume 11:Issue 5(2017)
• Page Start: 596
• Page End: 603
• Publication Date: 2017-07-01
• Subjects: particle filtering (numerical methods) -- iterative methods -- smoothing methods -- signal sampling; particle filtering method -- adaptive iteration strategy -- one‐step particle smoother -- proper weighted samples -- importance sampling -- current measurement information -- a priori distribution -- iteration process; Signal processing -- Periodicals; 621.3822
• DOI: 10.1049/iet-spr.2016.0194
• Languages: English
• ISSNs: 1751-9675

Abstract

Abstract : A new one‐step particle smoother is explicitly given in the form of proper weighted samples. It is employed iteratively to improve the importance sampling in particle filtering through incorporating the current measurement information into the a priori distribution. An adaptive iteration strategy is proposed to accelerate the running, which introduces a parameter into the weight increment to adjust the iteration process. Then, new particle filtering method can be constructed through combining the one‐step smoothing and the adaptive iteration strategy.