Application of adaptive Kalman filter technique in initial alignment of strapdown inertial navigation system

In order to improve the alignment precision and convergence speed of strap-down inertial navigation system, an initial alignment method based on Sage-Husa adaptive filter is presented. We also derived the exactitude alignment error model and adaptive Kalman filter equation in the azimuth of small misalignment angle. As usual, known the noise statistical characteristics, Kalman filter is suitable; but in the active system most noise statistical characteristics are unknown, in this case, we introduce the adaptive Kalman filter. It uses the information of observed data, on-line estimation noise statistical characteristics and state simultaneously in order to improve the filter continuously, so, the filter has a higher estimation accuracy than the conventional Kalman filter. By simulating verifying, the adaptive Kalman filter enhances the convergence speed and alignment accuracy effectively.