Abstract
Inertial Measurement Unit (IMU) calibration accuracy is easily affected by turntable errors, so the primary aim of this study is to reduce the dependence on the turntable’s precision during the calibration process. Firstly, the indicated-output of the IMU considering turntable errors is constructed and with the introduction of turntable errors, the functional relationship between turntable errors and the indicated-output was derived. Then, based on a D-suboptimal design, a calibration method for simultaneously identifying the IMU error model parameters and the turntable errors was proposed. Simulation results showed that some turntable errors could thus be effectively calibrated and automatically compensated. Finally, the theoretical validity was verified through experiments. Compared with the traditional method, the method proposed in this paper can significantly reduce the influence of the turntable errors on the IMU calibration accuracy.
Highlights
Strapdown inertial navigation systems (SINSs) are fully self-contained navigation systems that can continuously provide attitude, velocity and position information
For multi-position calibration of an inertial measurement unit (IMU) on a turntable, the norm of the angular rates and of the specific forces measured by the accelerometers and the gyros respectively are equal to the angular rates and the specific forces uniform distribution produced by the gravity, and angular rate produced by outer axis of the turntable, which means that the input components of the accelerometers and the gyros are distributed on spherical surfaces
This paper studies an IMU calibration method for overcoming the impacts of turntable errors, including the axis perpendicularities, zero position errors, mounting errors between the IMU and the turntable, on IMU calibration accuracy
Summary
Strapdown inertial navigation systems (SINSs) are fully self-contained navigation systems that can continuously provide attitude, velocity and position information. The separated calibration method has the advantage of high precision, but its calibration accuracy for model parameters is affected by turntable errors and IMU mounting errors. In reference [29], the derivative properties of norm-observation together with a model of the sensors are used to construct a cost function, which is minimized with respect to the unknown model parameters using Newton’s method, requiring no mechanical platform for the accelerometer calibration and only a simple rotating table for the gyro calibration. In systematic calibration, though the non-orthogonal angles or installation errors between the turntable axes of the rotating mechanism for RINS can be calibrated, but cannot be identified at the same time. Based on the D-suboptimal criterion, the calibration scheme was designed to simultaneously identify the IMU error parameters and the turntable errors, and automatically compensate for the turntable errors affecting IMU calibration accuracy
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