A Novel Robust Student's t-Based Kalman Filter

Authors: Yulong Huang, Yonggang Zhang, Ning Li, Zhemin Wu, Jonathon A. Chambers - IEEE Transactions on Aerospace and Electronic Systems 2017 cited by 478

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.