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一种非线性GM-PHD滤波新方法
引用本文:王品,谢维信,刘宗香,李鹏飞.一种非线性GM-PHD滤波新方法[J].电子学报,2012,40(8):1597-1602.
作者姓名:王品  谢维信  刘宗香  李鹏飞
作者单位:1. 深圳大学ATR国防科技重点实验室,广东深圳,518060
2. 防空兵指挥学院,河南郑州,450052
基金项目:国防预研基金(No.51326030204);国家重点实验室基金(No.9140C8004011007);国家科技支撑计划项目(No.2011BAH201302,No.2011BAH20B03)
摘    要:为了解决目标数未知情况下的多目标跟踪问题,提出了一种非线性条件下的高斯混合概率假设密度滤波新方法.该方法利用三阶球面容积-径向采样规则计算目标状态的概率分布特性,解决了状态方程和观测方程的非线性计算问题,利用模糊门限对滤波器的剪枝方法进行了优化,避免了高斯项数目的指数增长,利用观测数据生成新目标密度,使滤波器具备了对观测空间任意位置随机出现新目标的跟踪能力.通过仿真实验比较了四种非线性高斯混合概率假设密度滤波方法的性能,实验结果验证了提出算法的有效性.

关 键 词:多目标跟踪  随机有限集  概率假设密度滤波器  容积卡尔曼滤波  模糊门限
收稿时间:2011-12-27

A Novel Gaussian Mixture PHD Filter for Nonlinear Models
WANG Pin , XIE Wei-xin , LIU Zong-xiang , LI Peng-fei.A Novel Gaussian Mixture PHD Filter for Nonlinear Models[J].Acta Electronica Sinica,2012,40(8):1597-1602.
Authors:WANG Pin  XIE Wei-xin  LIU Zong-xiang  LI Peng-fei
Affiliation:1.ATR Lab,Shenzhen University,Shenzhen,Guangdong 518060,China;2.Air Defense Forces Command Academy,Zhengzhou,Henan 450052,China)
Abstract:To solve the problem of multi-target tracking model with the time-varying number of targets,a novel Gaussian mixture PHD filter is proposed for the nonlinear Gaussian system.A third-degree Spherical-Radial rule is applied to calculate the prediction and update distributions of target states for nonlinear multi-target models.The pruning method is optimized by using a fuzzy threshold to avoid the exponential increasing of the Gaussian components.The measurements are used to generate the density of new targets that appear randomly anywhere in the observation space.The performance of the four nonlinear Gaussian Mixture PHD filters is compared.The simulation results demonstrated the efficiency of the proposed algorithm.
Keywords:multi-target tracking  random sets  PHD filter  cubature Kalman filter  fuzzy threshold
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