Online self-calibration of FOG for rotational inertial navigation system

To address the issue of the calibration of the fiber optical gyros of the rotational inertial navigation system, we designed the recursive least square (RLS) estimation algorithm based on rotational inertial measurement unit and related online calibration method to calibrate the error parameters of fiber optic gyros (FOG) online. The initial alignment of the inertial navigation system can be improved based on the calibration results. For the initial alignment based on Kalman filter, a reduced-order model was proposed to decrease the amount of filtering calculations; For the initial alignment based on parameter recognition, the calibrated parameters can be used to calculate the equivalent gyro bias, and thereby, decrease the approximation error of initial azimuth error. Because the procedure processing signal outputted by each gyro is independent and is of symmetry, applying time division multiplexing to the RLS solver in hardware implementation, the resources for RLS solver can be reduced by 2/3. And the internal divider and trigonometric function solver can be further optimized by time division multiplexing. The proposed calibration method is of high precision, helps to improve the initial alignment, and is apt to be implemented with hardware, and thus, is of good practicality in engineering application.