An adaptive filtering algorithm for unknown non-Gaussian measurement noise
Konferenz: ECITech 2022 - The 2022 International Conference on Electrical, Control and Information Technology
25.03.2022 - 27.03.2022 in Kunming, China
Tagungsband: ECITech 2022
Seiten: 5Sprache: EnglischTyp: PDF
Autoren:
Liu, Qitao (Northwestern Polytechnical University, Xi’an, China & Northwest Institute of Mechanical and Electrical Engineering Xi’an, China)
Chao, Hongxiao; Lei, Qiang; Cao, Zhiyuan (Northwest Institute of Mechanical and Electrical Engineering Xi’an, China)
Inhalt:
In order to solve the state estimation problem with non-Gaussian measurement, an adaptive filtering algorithm is proposed. The measurement noise is modeled by the heavy-tailed distribution. The variational Bayesian algorithm can be used to estimate the parameter of the measurement noise and the system state. Simulation results are presented to demonstrate the versatility and improved performance of the proposed adaptive filter over conventional Kalman filters and the lower complexity than the particle filters.