Design and Experimental Evaluation of integrated orientation estimation algorithm Autonomous Underwater Vehicle Based on Indirect Complementary Filter

This paper aims is to design an integrated navigation system constituted by low-cost inertial sensors to estimate the orientation of an Autonomous Underwater Vehicle (AUV) during all phases of under water and surface missions. The proposed approach relied on global positioning system, inertial measurement unit (accelerometer & rate gyro), magnetometer and complementary filter technique. Complementary filter operates based on low pass filter and high pass filter to remove noise and bias error of measurement data in the integrated navigation structure, respectively. Consequently, a relatively accurate orientation estimation is provided for guidance/control system. The most important feature of the proposed approach is the ability of switching between GPS and magnetometer sensor consistent with phase-change in the AUV motion. This brings about more accurate estimation of heading angle in both the surface and underwater phase compared to gyro-based navigation. The performance of the proposed algorithm is assessed in a field test executed on a research AUV and in comparison, with Kalman filter.