2024
DOI: 10.3390/app14041393
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An Improved Adaptive Iterative Extended Kalman Filter Based on Variational Bayesian

Qiang Fu,
Ling Wang,
Qiyue Xie
et al.

Abstract: The presence of unknown heavy-tailed noise can lead to inaccuracies in measurements and processes, resulting in instability in nonlinear systems. Various estimation methods for heavy-tailed noise exist. However, these methods often trade estimation accuracy for algorithm complexity and parameter sensitivity. To tackle this challenge, we introduced an improved variational Bayesian (VB)-based adaptive iterative extended Kalman filter. In this VB framework, the inverse Wishart distributionis used as the prior for… Show more

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