On-line sensing system of dynamic ship's attitude by use ofservo-type accelerometers

For an accurate automatic measurement of ship's attitude the paper proposes an intelligent online sensing system which uses four servo-type accelerometers and one servo-type inclinometer appropriately located on the ship. Through an adequate location of the accelerometers, the heaving, rolling, and pitching signals of the ship are separated from each other with adequate linear combinations of the four sensors' outputs. Furthermore, the inclinometer is utilized to extract a bias signal of the pitching. By introducing linear dynamic models and linear observation equations on the three signals, their online measurement is reduced to the state estimation of the linear dynamic systems. A bank of Kalman filters are used to execute the online state estimation and to overcome changes in parameters in the dynamic models with time