Abstract：A tracking algorithm based on probability density propagation which can deal with non-linear and non-Gaussian issues is proposed. The Gaussian mixture model is adopted to represent the prior density distribution, posterior density distribution and likelihood distribution. The unscented transformation is used to deal with the non-linear prediction and approximation method is used to achieve the posterior density distribution. Finally, the weighted centroid point of the posterior density distribution’s different modes is calculated and set as the current position of the target. Simulation results indicate that the proposed algorithm can deal with the tracking task in wireless sensor network under strong noise.
高庆华, 金明录, 王洁, 王洪玉. 一种基于概率密度传播的目标跟踪算法[J]. 电子与信息学报, 2010, 32(10): 2410-2414.
Gao Qing-Hua, Jin Ming-Lu, Wang Jie, Wang Hong-Yu. A Tracking Algorithm Based on Probability Density Propagation. , 2010, 32(10): 2410-2414.
2010, Vol. 32 
