The study of square root cubature Kalman smoother and its application on INS/GPS integrated navigation

Smoother is a method of improving filtering accuracy more. Standard Gaussian filter and Gaussian smoother formulation is presented in this article. With respect to high dimensional state space model, CKF is an algorithm design with more superiority. Its high stable style of square root CKF is depicted, accordingly square root FI-CKS theory derivation and the flow are deduced. Then the proposed smoother is applied to INS/GPS integrated navigation with large misalignment. The track of INS is first generated, and then SR-CKF, SR-FI-CKS is applied at simulated INS data, under the same condition, making a comparison with UKF, URTSS, FI-EKS, CKF and FI-CKS. The outcomes indicate that FI-EKS diverges while definite sampled nonlinear smoothers are convergent. Especially SR-FI-CKS operates with smoothly and stability, and gives out the highest accuracy on the performance of longitude and latitude estimation.