A Fast Initial Alignment Method for SINS on Stationary Base

In case of initial self-alignment for SINS on stationary base, when the level accelerometer Outputs are taken as the measurement value for Kalman filter, the convergence speed of azimuth misalignment angle is limited by the observability of SINS. A fine alignment method for SINS is introduced firstly, which can do the accelerometer-based leveling alignment and gyro-based heading alignment simultaneously. The observability analysis by Singular Value Decomposition for this method shows that, the degree of observability of SINS is improved by adding observable extern information. Based on the analysis, a fast initial alignment method is proposed, which employs a reduced order alignment Kalman filter and takes both the level accelerometer outputs and cast gyroscope output as the measurement value. Besides, the model error compensation method is given. Simulation and experimental comparison results between this fast alignment method and traditional one illustrate that, the convergence speed of azimuth misalignment angle is improved greatly with good real-time performance.