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A rotational inertial navigation system (RINS) could improve navigation performance by modulating the inertial sensor errors with rotatable gimbals. When an inertial measurement unit (IMU) rotates, the deviations between the accelerometer-sensitive points and the IMU center will lead to an inner lever-arm effect. In this paper, a self-calibration method of the inner lever-arm parameters for a tri-axis RINS is proposed. A novel rotation scheme with variable angular rate rotation is designed to motivate the velocity errors caused by the inner lever-arm effect. By extending all inner lever-arm parameters as filter states, a Kalman filter with velocity errors as measurement is established to achieve the calibration. The accuracy and feasibility of the proposed method are illustrated by both simulations and experiments. The final results indicate that the inner lever-arm effect is significantly restrained after compensation by the calibration results.

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In high-precision navigation applications, a well-designed self-calibration method is a convenient approach to ensuring the positioning performance of a rotational inertial navigation system (RINS). Benefiting from the gimbal structure, traditional inertial measurement unit (IMU) sensor errors, including gyro drifts, accelerometer biases, scale factor errors and installation errors, could be estimated through a filter process under a proper rotation scheme. However, when the IMU rotates, inner lever-arm effects may bring additional errors to the observations, which may reduce the self-calibration accuracy. In this paper, an improved self-calibration method that includes consideration of the inner lever-arm effect is proposed for a dual-axis RINS. Based on analysis of the error propagation characteristics, a novel rotation scheme with variable angular rate is designed. By adopting the proposed self-calibration method, traditional IMU sensor errors can achieve much higher accuracy, and the inner lever-arm parameters can also be well calibrated simultaneously. Long-term vehicle navigation indicates that the positioning accuracy was significantly enhanced after the compensation of the calibration results, fully illustrating the effectiveness of the proposed method in ameliorating navigation performance for the dual-axis RINS.

Benefiting from frame structure, RINS can improve the navigation accuracy by modulating the inertial sensor errors with proper rotation scheme. In the traditional motor control method, the measurements of the photoelectric encoder are always adopted to drive inertial measurement unit (IMU) to rotate. However, when carrier conducts heading motion, the inertial sensor errors may no longer be zero-mean in navigation coordinate. Meanwhile, some high-speed carriers like aircraft need to roll a certain angle to balance the centrifugal force during the heading motion, which may result in non-negligible coupling errors, caused by the FOG installation errors and scale factor errors. Moreover, the error parameters of FOG are susceptible to the temperature and magnetic field, and the pre-calibration is a time-consuming process which is difficult to completely suppress the FOG-related errors. In this paper, an improved motor control method with the measurements of FOG is proposed to address these problems, with which the outer frame can insulate the carrier's roll motion and the inner frame can simultaneously achieve the rotary modulation on the basis of insulating the heading motion. The results of turntable experiments indicate that the navigation performance of dual-axis RINS has been significantly improved over the traditional method, which could still be maintained even with large FOG installation errors and scale factor errors, proving that the proposed method can relax the requirements for the accuracy of FOG-related errors.