A Novel Calibration Method for SINS and DVL Based on Improved Dung Beetle Optimizer

The calibration quality of the Doppler velocity log (DVL) significantly impacts the performance of the strap-down inertial navigation system (SINS)/ DVL-integrated navigation system. Optimizer-based calibration algorithms consider the installation misalignment angle and scale factor error as optimization objectives, thus simplifying the calibration process into an optimizer problem. However, optimizer-based calibration under large installation misalignment angle suffers from slow convergence speed and local optima issues problems. To address these challenges, this article proposes a novel calibration algorithm for estimating installation misalignment angle and scale factor error between SINS and DVL sensors based on an improved dung beetle optimizer (DBO). A novel multistrategy integration is designed in the dung beetle optimizer algorithm to balance the exploration and exploitation during optimization. Due to fast and accurate optimization, this calibration algorithm streamlines calibration times and removes the necessity for specialized vehicle operations. Both simulation and sea trials demonstrate the capability of the algorithm to rapidly and accurately estimate scale factor error and misalignment angle, thereby significantly improving navigation accuracy.