舰船电子工程2019，Vol.39Issue(9)：32-36,100,6.DOI:10.3969/j.issn.1672-9730.2019.09.008
基于UKF-GM-PHD滤波算法的非线性多目标跟踪方法研究∗
Research of Nonlinear Multi-target Tracking Method Based on UKF-GM-PHD Filtering Algorithm
摘要
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.关键词
高斯混合概率假设密度/无迹卡尔曼滤波/多目标跟踪Key words
gaussian mixture probability hypothesis density/unscentesd kalman filter/multiple targets tracking分类
信息技术与安全科学引用本文复制引用
齐海明,张安清..基于UKF-GM-PHD滤波算法的非线性多目标跟踪方法研究∗[J].舰船电子工程,2019,39(9):32-36,100,6.基金项目
国家自然科学基金项目(编号:61303192)资助. （编号:61303192）
