Self-Aided Navigation Strategy: An Underwater Integrated Navigation Algorithm Based on INS and Trajectory Constraints

Aiming at the problem that autonomous underwater vehicles (AUVs) can only rely on inertial navigation system (INS) for navigation in specific environments (noncooperative environments or extreme cases of external sensor failures, etc.) and that the navigation accuracy will decrease rapidly over time due to the cumulative nature of INS errors in the absence of external signal correction, this article proposes a self-aided navigation strategy. The core idea of this strategy is to deeply explore the characteristics of INS itself by perceiving the AUV’s motion characteristics and environmental changes, extract navigation-related auxiliary information, and fuse this information with the INS to correct the accumulated error of the INS during the AUV’s long navigation process, as well as to provide a reliable priori state for the subsequent navigation. This article combines theoretical analysis, mathematical simulation, and field experiments to comprehensively verify the self-aided navigation strategy under circular motion trajectory constraints. The experimental results show that the strategy realizes the correction of INS attitude and velocity, effectively delays the INS error dispersion, improves the autonomous navigation capability in the absence of external correction signals, and provides new ideas and practical basis for the application of inertial navigation technology in long-endurance navigation specific environments.