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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: Target Tracking Algorithm Based on MCMC Extend Kalman Particle Filter
Source: 2010 Asia-Pacific Conference on Information Theory (APCIT 2010 E-BOOK) (pp 409-413)
Author(s): Huajian Wang, Department of Communication and Engineering, Engineering College of China Armed Police Force, Xi’an Shaanxi, China 710086
Abstract: Considering the problem of poor tracking accuracy and particle degradation in the traditional particle filter al- gorithm, a new improved particle filter algorithm with the Markov chain Monte Carlo (MCMC) and extended particle fil- ter is discussed. The algorithm uses Extend Kalman filter to generate a proposal distribution, which can integrate latest observation information to get the posterior probability distribution that is more in line with the true state. Meanwhile, the algorithm is optimized by MCMC sampling method, which makes the particles more diverse. The simulation results show that the improved extend Kalman particle filter solves particle degradation effectively and improves tracking accuracy.
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