A fast initial alignment for SINS based on disturbance observer and Kalman filter

Abstract

Initial alignment for a strap-down inertial navigation system (SINS) plays an important role in the following navigation and positioning operation. Initial alignment incorporates two stages: coarse and fine. This paper mainly investigates fine alignment for SINS under static base. A new fast SINS initial alignment scheme, a disturbance observer-based Kalman filter (DOBKF), is proposed to estimate the misalignment angles. As the name implies, the DOBKF is composed of a Kalman filter and a disturbance observer (DO). The Kalman filter is used to estimate horizontal misalignment angles, and the DO is applied to estimate the azimuth misalignment angle. In addition, when the estimations from the Kalman filter reach a steady state, they will be used as input for designing the DO. Compared with traditional filters, such as a Kalman filter used in initial alignment, the filter proposed by this paper not only greatly hastens the overall initial alignment process, but has comparable accuracy. Comparing simulation results shows that the proposed filter satisfies the requirement of SINS alignment.