Two-stage strong tracking filter with its application in transfer alignment

This paper deals with the transfer alignment problem of strapdown inertial navigation systems, using the velocity information and angular rate information of the ship. Major error sources for velocity-plus-angular rate matching is unmodeled ship body flexure dynamics. To reduce this alignment error, a two-stage strong tracking filter (TSTF) is designed. This TSTF is derived by merging the optimal two-stage Kalman filter with strong tracking filter. The ship body flexure is modeled as time-varying noise and its stochastic properties are estimated by TSTF. The simulation results show that the proposed method is effective to estimate the misalignment angles of the slave inertial navigation systems.