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Abstract. A rotary inertial navigation system requires higher calibration accuracy of some error parameters owing to rotation. Conventional multiposition and rotation calibration methods are limited, for they do not consider sensors' actual operating condition. In order to achieve these parameters' values as closely as possible to their true values in application, their influence on navigation is analyzed, and a relevant new calibration method based on a system's velocity output during navigation is designed for the vital error parameters, including inertial sensors' installation errors and the scale factor error of fiber optic gyro. Most importantly, this approach requires no additional devices compared to the conventional method and costs merely several minutes. Experimental results from a real dual-axis rotary fiber optic gyro inertial navigation system demonstrate the practicability and higher precision of the suggested approach. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

The navigation accuracy of the rotational inertial navigation system (RINS) could be greatly improved by periodically rotating the inertial measurement unit (IMU) with gimbals. However, error parameters in RINS should be effectively calibrated and compensated. In this paper, a self-calibration method is proposed for tri-axis RINS using attitude errors and velocity errors as measurements. The proposed calibration scheme is designed as three separate steps, and a certain gimbal rotates continuously in each step. All the error parameters in the RINS are calibrated when the whole scheme finishes. The separate calibration steps reduce the correlations between error parameters, and the observability of errors in this method is clear to demonstrate according to the relations between navigation errors and error parameters when gimbals rotate. Each calibration step only lasts 12 min, thus gyro drifts and accelerometers biases could be regarded as constant. The proposed calibration scheme is tested in both simulation and actual tri-axis RINS, and simulation and experimental results show that all 23 error parameters could be well estimated in tri-axis RINS. A long-term vehicle navigation experiment results show that after calibration and compensation, the navigation performance has doubled approximately, and the velocity accuracy is less than 2 m s −1 while the position accuracy is less than 1500 m, fully illustrating the significance of the proposed self-calibration method in improving the navigation performance of RINS.

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