Gaussian Mizture PHD Filter and Its Application in Multi-target Tracking
(0) In this paper, a filter model about Multi-target Tracking is present under the random set framework. Then the PHD filter is used to process the model and its closed-form is given under the linear Gaussian mixture situation. There exist two problems in PHD method. First is that the calculation is very heavy and increases exponentially. Second is the method can not identify the target and its trajectory. In order to solve the problems above, an optimized algorithm is shown to release the heavy load of calculating in PHD and a cluster analysis method is given to identify the target and its trajectory. In the last of the paper, the simulation is used to prove the efficiency of the method.
Multi-target tracking random set probability hypothesis density PHD
Zhi Wang Xiao-bin Xu Cheng-lin Wen
College of Automation, Hangzhou Dianzi University, Hangzhou 310018
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
2686-2691
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）