A Self-Calibration Method for Accelerometer Nonlinearity Errors in Triaxis Rotational Inertial Navigation System

• Published in: IEEE transactions on instrumentation and measurement Vol. 66; no. 2; pp. 243 - 253
• Main Authors: Gao, Pengyu, Li, Kui, Wang, Lei, Liu, Zengjun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accelerometer nonlinearity errors; Accelerometers; Accuracy; Calibration; Error analysis; Estimation; Gimbals; Inertial navigation; Inertial platforms; Kalman filters; Mathematical model; Navigation systems; Nonlinearity; Observability (systems); Parameters; Position errors; Position measurement; Rotation; rotation scheme design principle; rotational inertial navigation system (RINS); Self calibration; Teaching methods
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2016.2625958

The navigation performance of the rotational inertial navigation system (RINS) could be greatly improved by rotating the inertial measurement unit with gimbals, and self-calibration for error parameters could be achieved in RINS as well. However, accelerometer nonlinearity errors need to be considered and calibrated to further improve the navigation accuracy of RINS, especially in large dynamic applications. In this paper, a self-calibration method is proposed for accelerometer nonlinearity errors in triaxis RINS. Accelerometer nonlinearity errors and other errors are calibrated through optimal estimation with velocity and position error measurements. In order to guarantee that all errors are observable during calibration, some rotation scheme design principles are proposed, which are different from traditional observability analysis methods and could provide instructions for rotation scheme design directly. The effectiveness of the self-calibration method is proved by both simulation and experiment. The accelerometer nonlinearity errors could be accurately calibrated with the proposed method, while other error parameters reach higher calibration accuracy. Furthermore, experiment results from a long-term vehicle navigation show that velocity and position accuracy of the triaxis RINS have improved significantly after compensation with the self-calibration results, fully illustrating the significance of the proposed self-calibration method in improving the navigation performance of RINS.