Abstract
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.
Highlights
The errors of inertial sensors are the major cause which influences the accuracy of an inertial navigation system (INS)
The above calibration methods do not consider the effect of installation errors between the inertial measurement unit (IMU) and rotation axes, which affects the accuracy of attitude
A system-level self-calibration method for installation errors of a dual-axis rotational INS (RINS) was proposed in this paper
Summary
The errors of inertial sensors are the major cause which influences the accuracy of an inertial navigation system (INS). The above calibration methods do not consider the effect of installation errors between the IMU and rotation axes, which affects the accuracy of attitude. A self-calibration scheme, which included three separate steps to reduce the correlations between error parameters in tri-axis RINS, was designed [16]. Another study designed a self-calibration scheme for the gimbaled IMU, in which the multi-position and continuous rotation steps were processed alternately, the dynamic errors were suppressed, and the excitation was augmented [17]. A system-level self-calibration method for two types of installation errors of a dual-axis RINS is proposed to avoid the complicated separating calibration process. 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 (PWCS) method. The proposed self-calibration method is validated through simulation and experiment
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
