In-Motion Alignment Algorithm of Strapdown Inertial Navigation Systems

Abstract

Strapdown Inertial Navigation Systems (SINS) estimate position, velocity and angular orientation upon signals acquired by inertial sensors– accelerometers and gyroscopes - stiffly fixed on a vehicle. A SINS begins operating by the initialization process which provides initial position, velocity and alignment. The alignment algorithm estimates the SINS’s initial angular orientation with respect to local level Wander Azimuth frame. In general, the specialized literature deals with stationary alignment algorithms. This work presents an in-motion alignment algorithm based on work presented by Rogers (2003) considering azimuth’s angular deviation and inertial sensors bias estimations. In-motion alignment allows to restart the SINS after a long-time navigation, recovering system information accuracy and meeting the mission requirements without stopping the vehicle after, for instance, energy shutdowns or other failures. For warships the main advantage of in-motion alignment is to avoid delays in accomplishing missions or temporary vehicle’s exposures to potentially hazardous scenarios. The proposed in-motion alignment algorithm runs into two processes: coarse alignment and fine alignment. Both steps use Kalman Filters (KF) and aid sensors to improve estimation quality, providing position, velocity and attitude information with greater accuracy. An example of warship navigation is used to numerically validate the efficiency of the proposed algorithm.