A System-Level Self-Calibration Method for Installation Errors in A Dual-Axis Rotational Inertial Navigation System

• Main Authors: Shiyu Bai, Jizhou Lai, Pin Lyu, Xiaowei Xu, Ming Liu, Kai Huang
• Format: Article
• Language: English
• Published: MDPI AG 2019-09-01
• Series: Sensors
• Subjects: installation errors; system-level; self-calibration; observability analysis
• Online Access: https://www.mdpi.com/1424-8220/19/18/4005

In a dual-axis rotational inertial navigation system (RINS), there are two kinds of installation errors, nonorthogonal installation errors of inertial sensors, and installation errors between the inertial measurement unit (IMU) and rotation axes. Traditionally, these two errors are not considered simultaneously. Thus, they are calibrated separately by different estimation algorithms and rotation schemes. In this paper, a system-level self-calibration method for installation errors of a dual-axis RINS is proposed. Based on the Kalman filter, the measurement model is reestablished to ensure that all installation errors can be estimated together. First, the relationship between the initial attitude and subsequent attitude of IMU during rotation is used as a constraint to estimate nonorthogonal installation errors of accelerometers, and installation errors between the IMU and rotation axes. Then, the angular rate of the rotation mechanism is used as a reference to estimate nonorthogonal installation errors of the gyros. The rotation scheme of the IMU is designed to make all installation errors observable, and the observability of the system is analyzed based on the piecewise constant system method. Simulation and laboratory experiment results suggest that installation errors can be effectively estimated by the proposed method, thereby avoiding the complex separating process.