A Novel Robust Student's t-Based Kalman Filter

A novel robust Student's t-based Kalman filter is proposed by using the variational Bayesian approach, which provides a Gaussian approximation to the posterior distribution. Simulation results for a manoeuvring target tracking example illustrate that the proposed filter has smaller root mean sq...

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Bibliographic Details
Published inIEEE transactions on aerospace and electronic systems Vol. 53; no. 3; pp. 1545 - 1554
Main Authors Yulong Huang, Yonggang Zhang, Ning Li, Zhemin Wu, Chambers, Jonathon A.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Approximation
Bayesian analysis
Covariance matrices
Gaussian approximation
Gaussian distribution
heavy-tailed noises
Kalman filtering
Kalman filters
Mean square values
Noise measurement
Pollution measurement
Robustness
Simulation
State-space methods
Student's <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">t distribution
Time measurement
Tracking
variational Bayesian
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Summary:A novel robust Student's t-based Kalman filter is proposed by using the variational Bayesian approach, which provides a Gaussian approximation to the posterior distribution. Simulation results for a manoeuvring target tracking example illustrate that the proposed filter has smaller root mean square error and bias than existing filters.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2017.2651684