Abstract
The initial alignment model of Strapdown Inertial Navigation System (SINS) with large misalignment angle is a linear and nonlinear mixed system model. Aiming at the model, an improved Cubature Kalman Filter(CKF) algorithm is adopted. Firstly, the initial alignment model of SINS is established and analyzed. Then, singular value decomposition (SVD) is used to assist Cholesky decomposition to ensure numerical stability in the time update phase of the algorithm, while adjusting the modified covariance, and performing Kalman in the measurement update phase. Finally, the experimental results of initial alignment show that the improved CKF can deal with the SINS initial alignment problem well. The filtering accuracy is comparable to the CKF estimation accuracy, and the solving speed is better than the CKF.
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