噪声野值下的学生t分布混合CPHD滤波

doi:10.19665/j.issn1001-2400.2019.05.019

摘要/Abstract

摘要：

针对过程噪声和量测噪声野值导致高斯混合势概率假设密度滤波性能下降的问题,提出了一种基于学生t分布的势概率假设密度滤波。首先,引入学生t分布对重尾的过程噪声和量测噪声进行建模;其次,将多目标后验强度近似为学生t分布混合形式,推导了基于学生t分布的势概率假设密度滤波的闭合解,并采用矩匹配算法防止学生t分布的自由度无限增长。仿真结果表明,在含有过程噪声和量测噪声野值的环境下,所提算法的目标数估计精度和最优子模式分配距离优于高斯混合势概率假设密度滤波和学生t分布混合概率假设密度滤波,提高了多目标跟踪性能。

关键词: 噪声野值, 多目标跟踪, 势概率假设密度, 学生t分布

Abstract:

In order to solve the performance degradation of the Gaussian mixture cardinalized probability hypothesis density (GM-CPHD) filter induced by the process and measurement noise outlier, a novel CPHD filter based Student’s t distribution is proposed. The method introduces the Student’s t distribution to model the heavy tailed process and measurement noise. By approximating the multi-target posterior intensity as a Student’s t distribution mixture form, the linear closed-form solution of the CPHD is derived. Furthermore, the moment matching algorithm is used to prevent the infinite growth of the degree of freedom of the student’s t distribution. Simulation results demonstrate that the proposed filter can achieve a better target tracking performance than the GM-CPHD filter and the Student’s t distribution mixture probability hypothesis density filter under process and measurement noise outliers.

Key words: noise outlier, multi-target tracking, cardinalized probability hypothesis density, Student’s t distribution

中图分类号:

TN953

王明杰,姬红兵,刘龙. 噪声野值下的学生t分布混合CPHD滤波[J]. 西安电子科技大学学报, 2019, 46(5): 134-141.

WANG Mingjie,JI Hongbing,LIU Long. Student’s t Distribution mixture CPHD filter with noise outliers[J]. Journal of Xidian University, 2019, 46(5): 134-141.

图/表 5

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