Adaptive Kalman Filter Under Minimum Error Entropy with Fiducial Points for Strap-Down Inertial Navigation System/Ultra-Short Baseline Integrated Navigation Systems
Year: 2025
Type: article
Abstract: The integration of strap-down inertial navigation systems (SINSs) and ultra-short baseline (USBL) systems has become a mainstream navigation approach for unmanned underwater vehicles (UUVs). In shallow-sea environments, USBL measurements are frequently affected by complex non-Gaussian disturbances. Under such challenging conditions, traditional Kalman filters often exhibit limited performance in maintaining navigation accuracy. A novel adaptive Kalman filter is proposed to address this issue. The proposed method demonstrates significant robustness to complex non-Gaussian noise through the construction of an advanced regression model, the development of an adaptive free-parameter optimization scheme, and the implementation of a recursive filtering architecture incorporating entropy-based error correction. Comprehensive validation via numerical simulations and field experiments in offshore SINS/USBL integrated navigation scenarios demonstrates the superior robustness of the proposed method in complex underwater non-Gaussian noise environments.
DOI: 10.3390/jmse13050990
Authors: Boyang Wang, Zhenjie Wang
Institution: China University of Petroleum, East China
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Award: G7454614034
OpenAlex ID: W4410538909