计算机应用与软件2016，Vol.33Issue(11)：175-179,5.DOI:10.3969/j.issn.1000-386x.2016.11.041
基于高斯混合PHD滤波的多目标状态提取方法
MULTI-TARGET STATE EXTRACTION BASED ON GAUSSIAN MIXTURE PHD FILTER
摘要
Abstract
Gaussian mixture probability hypothesis density (GM-PHD)filter can effectively solve the problem of multi-target tracking un-der the condition of linear Gaussian model,while estimating the number of targets it also extracts the states of multi-target.The state extrac-tion precision of GM-PHD filter will drop down when it comes to the situation of closely spaced targets and too high clutter rate.In light of the performance degradation of GM-PHD in complex environments,we proposed an improved multi-target state extraction method of GM-PHD fil-ter.By modifying the update weight of Gaussian component and enhancing the merging criterion it reduces the interference caused by intensive targets and clutters.Simulation experimental results showed that the propose method is able to raise the precision of multi-target state estima-tion in different clutter environments.关键词
概率假设密度/高斯混合/多目标跟踪/状态提取Key words
Probability hypothesis density/Gaussian mixture/Multi-target tracking/State extraction分类
信息技术与安全科学引用本文复制引用
刘益,王平,高颖慧..基于高斯混合PHD滤波的多目标状态提取方法[J].计算机应用与软件,2016,33(11):175-179,5.基金项目
国家自然科学基金项目（61103082）。 （）
