SINS nonlinear initial alignment using Gauss-Hermite quadrature Kalman filter

In order to improve the precision and shorten the convergence time of SINS(strapdown inertial navigation system) initial alignment with a large azimuth misalignment angle, a simplified Gauss-Hermite quadrature Kalman filter (QKF) is introduced into the SINS initial alignment on a moving base. First, the configuration method for one-dimensional Gauss points and their corresponding coefficients in Gauss-Hermite quadrature is derived, which is then extended to form the multidimensional Gauss points and their coefficients using the direct tensor method. A simplified QKF is presented. Finally, by means of mathematical simulation, the filter performance of UKF(unscented Kalman filter) based on scaled symmetric sampling and QKF using 3 points in one dimension in SINS initial alignment with a large azimuth misalignment angle is compared, and the influence of different point numbers(3, 5 and 7) of one dimension on the QKF filter performance is also analyzed. The simulation results show that under the condition of a large azimuth misalignment angle on a moving base, the alignment accuracy of a 3-point QKF is much higher than that of the UKF, and the azimuth angle estimation error convergence rate of the three-point QKF is also much faster than that of the UKF. With the increase in the number of one-dimensional Gauss-Hermite quadrature points, the alignment accuracy of the QKF can be further improved.