Journal
IEEE SIGNAL PROCESSING LETTERS
Volume 23, Issue 4, Pages 468-472Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2016.2533543
Keywords
Gaussian approximate (GA) smoother; heavy-tailed noise; Student's t distribution; variational Bayesian (VB)
Categories
Funding
- National Natural Science Foundation of China [61371173]
- Fundamental Research Funds for the Central Universities of Harbin Engineering University [HEUCFQ20150407]
- Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [EP/K014307/1]
- EPSRC [EP/K014307/2] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K014307/2, EP/K014307/1] Funding Source: researchfish
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In this letter, a robust Gaussian approximate (GA) fixed-interval smoother for nonlinear systems with heavy-tailed process and measurement noises is proposed. The process and measurement noises are modeled as stationary Student's t distributions, and the state trajectory and noise parameters are inferred approximately based on the variational Bayesian (VB) approach. Simulation results show the efficiency and superiority of the proposed smoother as compared with existing smoothers.
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