New look at the Student's t-based Kalman filter from maximum a posterior perspective

被引:1
|
作者
Qin, Fangjun [1 ]
Chang, Lubin [1 ]
Zha, Feng [1 ]
机构
[1] Naval Univ Engn, Dept Nav Engn, Wuhan, Hubei, Peoples R China
来源
IET RADAR SONAR AND NAVIGATION | 2018年 / 12卷 / 08期
关键词
Kalman filters; maximum likelihood estimation; Bayes methods; probability; student t-based Kalman filter; STKF; Bayesian maximum a posterior perspective; linear system; heavy-tailed measurement noise; M-estimator; Cauchy function; likelihood probability density function; elliptical distribution;
D O I
10.1049/iet-rsn.2017.0422
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this study, the newly derived Student's t-based Kalman filter (STKF) is re-derived from Bayesian maximum a posterior perspective for linear systems with heavy-tailed measurement noises. This re-derivation reveals that the STKF is an M-estimator with Cauchy function as the robust cost function. The presented re-derivation can also be used as the unified procedure to derive robust Kalman-type filters by assuming the likelihood probability density function to be elliptical distributions.
引用
收藏
页码:795 / 800
页数:6
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