Initial Leveling with Input Estimation

Abstract

Initial leveling of strapdown inertial navigation system is essential in the distinguishing of gravity and acceleration effects, and in achieving accuracy. This paper proposes the application of a modified Kalman filter with and innovative recursive input estimator to a class of leveling problems, that are subject to abrupt environmental disturbances. The disturbance input is assumed to be arbitrary in starting time and of long duration and deterministic nature, such as the swelling of the sea for a seafaring vehicle. A hypothetical testing scheme is devised to detect the onset and presence of the disturbance input. The dynamic system has four states with color noise. The simulation results have demonstrated that the speed of convergence and accuracy are much improved as comparing to the original unmodified one.