Underwater integrated navigation technology based on SINS/LBL tight combination

As the exploitation of marine resources gains increasing global importance, Autonomous Underwater Vehicles (AUVs) have become essential tools due to their high autonomy and flexibility. To address the error accumulation problem in Strap-down Inertial Navigation Systems (SINS) and the potential signal interruptions in Long Baseline (LBL) acoustic positioning systems, this paper proposes a tightly coupled SINS/LBL integrated navigation method based on range-difference measurements. By using the difference between pseudo-ranges estimated by SINS and those measured by LBL as observations, and applying Kalman filtering for data fusion, the system maintains high navigation accuracy even under weak or intermittent LBL signals. The state and measurement models for the integrated system are formulated in detail. MATLAB simulations demonstrate that, compared to loosely coupled integration, the proposed tightly coupled method offers superior accuracy and robustness in estimating position, velocity, and attitude.