Improving self-alignment of strapdown INS using measurement augmentation

An alternative solution to the velocity based self-alignment of strapdown inertial navigation system is proposed. It is well known that a simple Kalman filter based solution to the above problem fails to provide accurate azimuth alignment due to the inherent lack of observability of the model in the presence of instrument bias. Earlier researchers use external digital filters to obtain improved estimation of selected states and substitute these into the filter. The current paper demonstrates that a simple augmentation of the output vector with the inertial measurement unit signals and an extended Kalman filter would yield similar or better alignment performance compared to such ad hoc additional digital filters. The proposed method improves the convergence rate of azimuth attitude error even in the presence of gyro bias and makes it relatively independent of the gyro noise. Results of comparative performance of the two filters using Monte Carlo simulation have been provided.