Single-axis Rotational SINS Navigation Algorithm with Motion Constraint for Land Vehicle System

Rotational strapdown inertial navigation system (SINS) is the most common high-precision autonomous navigation solution for land vehicles. Compared with dual-axis and tri-axis rotational schemes, the single-axis rotational scheme is relatively simple. The composition and error modulation of single-axis rotational SINS are given in this work, which indicate that the drift errors of the inertial measurement unit (IMU) in the rotational axis cannot be modulated. In order to constrain the accumulated errors caused by such drift errors, an inertial navigation algorithm with vehicle motion constraint for single-axis rotational SINS is proposed here. This work establishes a measurement equation for Kalman filtering using the non-holonomic constraint derived from the land vehicle motion model and, if available, odometer-derived speed. To evaluate the navigation performance of the proposed algorithm, road tests were conducted using a self-made fiber-optic single-axis rotational SINS. The results indicate that the proposed methodology is able to improve the navigational accuracy of single-axis rotational SINS significantly, especially the vehicle’s positioning accuracy.