A Novel Autonomous Initial Alignment Method for Strapdown Inertial Navigation System

Abstract

In-motion alignment of strapdown inertial navigation systems (SINS) without any geodetic-frame observations is one of the toughest challenges for autonomous vehicles. Considering the characteristics of SINS, this paper presents a dual-model-based in-motion alignment method for the odometer-aided SINS. Two inertial navigation calculation loops are established for an inertial measurement unit (IMU), one of which executes the in-motion gyrocompass horizontal alignment algorithm to decompose the body velocity measured by odometer to navigation frame and attenuate the disturbance. And the other is the attitude determination-based alignment loop, where the vector observation-based SINS alignment is executed. The contributions of the work presented here are twofold. First, the dual-model initial alignment (DMIA) algorithm for SINS is proposed, which introduces the idea of constructing multiple calculation loops for an IMU to maximize the advantages of SINS. Second, depending on the body-frame speed-aided attitude determination and navigation-frame speed-aided attitude determination, the body-frame velocity observation with disturbance is accurately decomposed to navigation frame with the noise attenuated by gyrocompass horizontal alignment. The experimental results show that the proposed DMIA algorithm can achieve a rapid and accurate in-motion alignment.