Dynamic Calibration Method for Autonomous Underwater Vehicle Using Improved ICCP Algorithm

摘要

INS (Inertial Navigation System) is a very important part of AUV (Autonomous Underwater Vehicle). The long-term position accuracy of INS is not satisfactory for the reason of accumulation of INS errors. So calibration signal such as GPS (Global Position System) signal is needed . Sea water blocks GPS signal so that AUV is demanded to ascend to sea surface to receive the signal. Continuity of mission will be ruined. To tackle this problem, a TM (Terrain Matching) solution is introduced, which can dynamically calibrate INS to achieve an "underwater, long-tern, high degree of accuracy " goal. A novel TM algorithm with combined method for updating matched data , evolved from ICCP (Iterative Closest Contour Point), is proposed in which a "memory factor" is included. Matching accuracy can be improved . Simulation results verify such benefits that the accuracy of improved ICCP has been enhanced by 96.8 % with the same times of iteration(5 times) comparing with ICCP.