Details

Autor(en) / Beteiligte

• He, An
• Min, Cui
• Peng, Zhang
• Peng, Liu
• Mengwei, Li
• Hua, Yongzhao
• Ren, Zhang
• Wang, Mengyi

Titel

SINS/USBL Calibration Method Based on Maximum Correntropy Under UKF Framework

Ist Teil von

• Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control, 2022, p.1695-1704

Ort / Verlag

Singapore: Springer Nature Singapore

Erscheinungsjahr

2022

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Non-Gaussian noise is a challenging problem in underwater calibration. Aiming at the calibration process of strapdown inertial navigation system (SINS)/ultra short baseline (USBL), a maximum correntropy criterion unscented Kalman filter (MCUKF) algorithm is proposed to deal with the interference of heavy tailed impulse noise in complex underwater environment. The prediction state estimation and covariance matrix are obtained by unscented transformation (UT). The measurement information is expressed by nonlinear regression method with maximum correlation criterion (MCC) cost function, which enhances the robustness of unscented Kalman filter(UKF) to impulse noise. Simulation results show that compared with other methods, this method has faster convergence speed and better calibration results.