The Labeled Multi-Bernoulli Filter for Multitarget Tracking With Glint Noise

被引：29

作者：

Dong, Peng ^{[1
]}

Jing, Zhongliang ^{[1
]}

Leung, Henry ^{[2
]}

Shen, Kai ^{[1
]}

Li, Minzhe ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Shanghai 200240, Peoples R China

[2] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB T2N 1N4, Canada

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2019年 / 55卷 / 05期

基金：

中国国家自然科学基金; 国家自然科学基金重大项目;

关键词：

Noise measurement; Radio frequency; Target tracking; Gaussian distribution; Gamma distribution; Covariance matrices; Bayes methods; Glint noise; labeled multi-Bernoulli (LMB) filter; multitarget tracking (MTT); EXTENDED TARGET TRACKING; RANDOM FINITE SETS; ALGORITHM;

D O I：

10.1109/TAES.2018.2884183

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

A labeled multi-Bernoulli (LMB) filter is presented to perform multitarget tracking (MTT) for the glint noise. The measurement noise is modeled as a multivariate Student-t process. The variational Bayesian method is applied in the LMB framework with the augmented state. The predictive likelihood is calculated via minimizing the Kullback-Leibler divergence by the variational lower bound. Simulation results show that our approach is effective in MTT with the glint noise.

引用

页码：2253 / 2268

页数：16

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