A new fast and precision approach for SINS stationary self-alignment

For the poor observability of azimuth misalignment angle and east gyro drift rate of the traditional initial alignment, a new strapdown inertial navigation system (SINS) stationary fast self-alignment approach is proposed by means of analyzing the characteristic of SINS stationary alignment seriously. The new approach takes full advantage of the specific force and angular velocity information given by inertial measurement unit (IMU) instead of the mechanization of SINS, which makes the approach much more efficient. Firstly, coarse alignment algorithm is presented. Secondly, a new fine alignment model for SINS stationary self-alignment is derived, and the observability of the model is analysed. Then, a modified Sage-Husa adaptive Kalman filter is introduced to estimate the misalignment angles. Finally, some computer simulation results illustrate the efficiency of the new approach and its advantages, such as higher alignment accuracy, shorter alignment time, self-contained and less calculation.