Application of Kalman filtering to the calibration and alignment of inertial navigation systems

Abstract

The development of Kalman filters for the calibration and alignment of complex inertial guidance systems is presented. The attitude error equation is augmented by gyro and accelerometer model parameters. The mechanization of the algorithm involves preprocessing the raw measurements to reduce the computational load. Results for simulated data show that preprocessing has very little effect on the performance of the filter. Other topics discussed include gyro and accelerometer models and a technique for generating parameter excitation trajectories.