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A multiple maneuvering targets tracking algorithm based on a generalized pseudo-Bayesian estimator of first order 被引量:1
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作者 shi-cang ZHANG Jian-xun LI +1 位作者 Liang-bin WU chang-hai shi 《Journal of Zhejiang University-Science C(Computers and Electronics)》 SCIE EI 2013年第6期417-424,共8页
We describe the design of a multiple maneuvering targets tracking algorithm under the framework of Gaussian mixture probability hypothesis density(PHD) filter.First,a variation of the generalized pseudo-Bayesian estim... We describe the design of a multiple maneuvering targets tracking algorithm under the framework of Gaussian mixture probability hypothesis density(PHD) filter.First,a variation of the generalized pseudo-Bayesian estimator of first order(VGPB1) is designed to adapt to the Gaussian mixture PHD filter for jump Markov system models(JMS-PHD).The probability of each kinematic model,which is used in the JMS-PHD filter,is updated with VGPB1.The weighted sum of state,associated covariance,and weights for Gaussian components are then calculated.Pruning and merging techniques are also adopted in this algorithm to increase efficiency.Performance of the proposed algorithm is compared with that of the JMS-PHD filter.Monte-Carlo simulation results demonstrate that the optimal subpattern assignment(OSPA) distances of the proposed algorithm are lower than those of the JMS-PHD filter for maneuvering targets tracking. 展开更多
关键词 Gaussian mixture PHD filter Jump Markov system Generalized pseudo-Bayesian estimator of first order(GPB1) Multi-target tracking
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