Research of Nonlinear Multi-target Tracking Method Based on UKF-GM-PHD Filtering Algorithm
QI Haiming
ZHANG Anqing
Abstract：At present,multi-target tracking technology based on Probability Hypothesis Density(PHD)filtering has become a hot field in multi-target tracking research. In this paper,the traditional nonlinear processing method Unscentesd Kalman Filter (UKF)and Gaussian Mixture PHD(GM-PHD)filtering algorithm are combined to propose UKF-GM-PHD filtering algorithm. Thereby the application of GM-PHD filter in nonlinear systems is realized. The effectiveness of the proposed algorithm is verified by simulation. The algorithm is compared with the Extended Kalman Filter GM-PHD(EKF-GM-PHD)filtering algorithm. The filter?ing accuracy of the algorithm is higher than that of EKF-GM-PHD filtering algorithm.
Keywords：gaussian mixture probability hypothesis densityunscentesd kalman filtermultiple targets tracking
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 32-36,100 )