厚尾噪声条件下的学生t泊松多伯努利混合滤波器  

A Student’s t Poisson multi-Bernoulli mixture filter in the presence of heavy-tailed noise

作　　者：赵子文[1] 陈辉[1] 连峰[2] 张光华[2] ZHAO Zi-wen;CHEN Hui;LIAN Feng;ZHANG Guang-hua(School of Electrical and Information Engineering,Lanzhou University of Technology,Lanzhou Gansu 730050,China;School of Automation Science and Engineering,Xi’an Jiaotong University,Xi’an Shaanxi 710049,China)

机构地区：[1]兰州理工大学电气工程与信息工程学院,甘肃兰州730050 [2]西安交通大学自动化科学与工程学院,陕西西安710049

出　　处：《控制理论与应用》2024年第9期1598-1609,共12页Control Theory & Applications

基　　金：国家自然科学基金项目(62163023,61873116,62173266,62103318);甘肃省教育厅产业支撑计划项目(2021CYZC-02);甘肃省教育厅优秀研究生“创新之星”项目(2022CXZX-468);2023年甘肃省军民融合发展专项资金项目,2024年甘肃省重点人才项目资助.

摘　　要：针对运动过程和观测过程均受到异常噪声干扰的复杂不确定性多目标跟踪问题,本文创新性地提出了学生t混合泊松多伯努利混合滤波器.首先,直接将广域分布的异常噪声特性建模为学生t分布.随后,将泊松多伯努利混合滤波器的泊松点过程(PPP)和多伯努利混合(MBM)的概率密度参数合理的近似为学生t混合形式.其次,基于多目标概率密度的学生t混合模型,详细推导了泊松多伯努利混合滤波器学生t混合共轭先验形式,建立了学生t混合泊松多伯努利混合的闭式递推框架.最后,通过带显著拖尾分布特性的过程噪声和量测噪声共同干扰的复杂多目标跟踪仿真实验,验证了所提滤波算法的有效性.Aiming at the complex uncertainty multi-target tracking where both the motion process and observation process are disturbed by anomalous noise,this paper innovatively proposes a Student’s t mixture Poisson multi-Bernoulli mixture filter.First,the anomalous noise characteristics of the wide-area distribution are directly modeled as the Student’s t distribution.Subsequently,the probability density parameters of the Poisson point process(PPP)and the multi-Bernoulli mixture(MBM)of the Poisson multi-Bernoulli mixture filter are reasonably approximated by the Student’s t mixture form.Moreover,based on the Student’s t mixture model which approximates the multi-target probability density,the Student’s t mixture conjugate prior form of Poisson multi-Bernoulli mixture filter is derived in detail and a closed-form recursive framework of Student’s t mixture Poisson multi-Bernoulli mixture is established.Finally,the effectiveness of the proposed filtering algorithm is verified by complex multi-target tracking simulation experiments under the joint interference of process noise and measurement noise with significant trailing distribution characteristics.

关 键 词：随机有限集 多目标跟踪 学生t混合 厚尾噪声 泊松多伯努利混合 

分 类 号：TN713[电子电信—电路与系统] TN957.51