Cubature Gaussian Particle Filter for Initial Alignment of Strapdown Inertial Navigation System

The error model of the initial alignment of the marine strap down inertial navigation system on the swaying base is nonlinear, while the azimuth angle error is large. For this nonlinear model, a new nonlinear filter called as the cubature Gaussian Particle filter is proposed, which is based on the cubature Kalman filter and the Gaussian Particle filter. The cubature Kalman filter is used to calculate the estimate value and the covariance matrix in the observation update for the distribution function, which is sampled as the importance density function for the Gaussian Particle filter. The simulation results demonstrate the novel filter has better estimation performance than the unscented Kalman filter and the Gaussian Particle filter in the initial alignment.