Gaussian mixture PHD filter and its application in Multi-target Tracking

Author

Wang, Zhi ; Xu, Xiao-bin ; Wen, Cheng-lin

Author_Institution

Coll. of Autom., Hangzhou Dianzi Univ., Hangzhou, China

fYear

2009

fDate

17-19 June 2009

Firstpage

2686

Lastpage

2691

Abstract

In this paper, a filter model about multitarget 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.

Keywords

Gaussian processes; aerospace control; position control; probability; statistical analysis; target tracking; cluster analysis method; linear Gaussian mixture; multitarget tracking; probability hypothesis density filter; target identification; target trajectory; Algorithm design and analysis; Automation; Clustering algorithms; Educational institutions; Filtering; Nonlinear filters; Optimization methods; Target tracking; Trajectory; Multi-target tracking; probability hypothesis density PHD; random set;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference, 2009. CCDC '09. Chinese

Conference_Location

Guilin

Print_ISBN

978-1-4244-2722-2

Electronic_ISBN

978-1-4244-2723-9

Type

conf

DOI

10.1109/CCDC.2009.5195062

Filename

5195062