Application of Modified Self-Adaptive Kalman Filter in Integrated Navigation System of Autonomous Underwater Vehicle
Owing to the complex operating environment of underwater vehicles, many uncertainties of sensors data, big noises of sensors , low precision and high rate of wild points of underwater acoustic sensors, data processing of motion sensors data for underwater vehicle navigation system becomes extremely important. The integrated navigation system of autonomous underwater vehicle based on dead-reckoning is introduced. An modified adaptive Kalman filter is adopted for underwater vehicle sensors information data processing. Experimental results show that the modified self-adaptive Kalman filter(SAKF) is effective, and can meet the underwater robots perform a variety of tasks in the navigation and positioning accuracy..
Yiyi Zhouzhou and Qi Luo
Y. S. Sun et al., "Application of Modified Self-Adaptive Kalman Filter in Integrated Navigation System of Autonomous Underwater Vehicle", Applied Mechanics and Materials, Vol. 79, pp. 298-303, 2011