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2010 Asia-Pacific Conference on Information Theory (APCIT 2010 E-BOOK)

Xi'an,China,10.1-10.2,2010

ISBN: 978-1-935068-47-1 Scientific Research Publishing, USA

E-Book 506pp Pub. Date: November 2010

Category: Computer Science & Communications

Price: $80

Title: A Novel Algorithm Based on MCMC Extend Kalman Particle Filter
Source: 2010 Asia-Pacific Conference on Information Theory (APCIT 2010 E-BOOK) (pp 283-287)
Author(s): Huajian Wang, Dept. of Communication and Engineering, Engineering College of China Armed Police Force Xi’an Shaanxi, China 710086
Abstract: As the problem of tracking accuracy poor and particle degradation in the traditional Particle Filter algorithm, a new improved Particle Filter algorithm with the Markov chain Monte Carlo (MCMC) and extended Particle Filter is discussed. The algorithm uses Extend Kalman filter to generate a proposal distribution, which can integrate latest observation information. Meanwhile, the algorithm is optimized by MCMC sampling method, which makes the particles more diversification. The simulation results show that the improved Extend Kalman Particle Filter solves particle degradation effectively and improves tracking accuracy.
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