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| Research of Multiple Model Particle Filter Tracking Algorithms |
| Jian Fu-sheng①②③; Xu Yue-min②; Yin Ze-jie① |
| ①University of Science and Technology of China, Hefei 230026, China; ②Center for Space Science and Applied Research, CAS, Beijing 100190, China; ③Unit 92323 of PLA, Qingdao 266003, China |
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Abstract An Enhanced Multiple Model Particle Filter(EMMPF) algorithm is presented for maneuvering target tracking. Rather than allocating the particles to the various modes according to mode probabilities as the MMPF, the new algorithm proposes an approach which enables the user to control the number of particles in a certain mode flexibly without interaction between particles of different mode. The estimations of mode and state are calculated respectively, and the posterior probability of each model is updated with the model likelihood function. It is demonstrated that the new algorithm can achieve better performance with less particles, compared with MMPF.
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Received: 05 June 2009
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Corresponding Authors:
Jian Fu-sheng
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2010, Vol. 32 
