A High-Precision System-Level Calibration Method for IMU Full Parameters Estimation Based on a Simplified Ten-Position Rotation Scheme

Abstract

To improve the navigation accuracy of inertial measurement units (IMUs), a system-level full-parameter calibration method based on a dual-observation ten-position rotation scheme, which integrates attitude–velocity matching with a Kalman filter algorithm, is proposed in this article. Compared with the conventional 29-position calibration scheme, the proposed method achieves high-precision estimation of all IMU parameters while reducing the total calibration time from 63 to 22 min, thereby significantly enhancing calibration efficiency. First, comprehensive error models for the gyroscope and accelerometer are established, including scale factor errors, nonorthogonality, sensor-to-turntable misalignment, gyro and accelerometer biases, lever-arm offsets, and quadratic errors. Second, a simplified ten-position rotation scheme is designed to maximize the excitation of each error component under limited test configurations. Finally, Kalman filtering is performed using attitude and velocity matching to estimate the IMU error parameters. System-level simulations and experimental tests verify the effectiveness and applicability of the proposed algorithm. Both simulation and experimental results demonstrate that all IMU error parameters are estimated by the proposed method, and the correctness and practical feasibility of the proposed calibration scheme are verified by the designed tests.