On-line calibration method of SINS/DVL integrated navigation system

Abstract

In this paper, the question of integrated navigation system calibration has been researched. Based on the principle of DVL velocity measurement, we analyzed the error source, and constructed the DVL error model based on the scale factor and misalignment angle between SINS and DVL. Based on the DVL error model and the SINS navigation error model, an integrated navigation system model has been established. And a corresponding Kalman filter model has been designed using the speed error as the observation. The observability analysis approach was used to analyze the observability of SINS/DVL integrated navigation system and the estimation of the misalignment angle and scale factor. It is verified the correctness of this method by digital simulation. The sufficient condition which the SINS/DVL integrated navigation system needs has been deduce in mathematics. The main conclusions are presented as following: the scale factor is observable when the carrier takes a movement with constant attitude and time-varying special force. And if the yaw-direction misalignment angle is only considered and the upward velocity is zero, the yaw-direction misalignment angle is observable when the carrier takes a linear movement with constant velocity. And the misalignment angles are observable when the carrier takes a movement with constant attitude and time-varying special force and linearly independent derivatives of special force for different time. Then, a method of implementing on-line calibration which contains of three types of exercise has been designed. Finally, the on-line calibration method provided in this paper was used to verify by the vessel tests. The experiment results shows that the SINS/DVL integrated on-line calibration method could effectively estimate the required all kinds of error sources. The error compensation can effectively suppress the accumulation of SINS error and improve the positioning accuracy of the SINS/DVL integrated navigation system. The finally positioning accuracy is better than 0.75%d.