Existing polar transfer alignment (TA) algorithms are designed based on linear Kalman filters (KF) to estimate misalignment angles. In the case of a large misalignment angle, these algorithms cannot be applied in order to achieve accurate TA. In this paper, a TA algorithm based on an unscented Kalman filter (UKF) is proposed to solve the problem of the large misalignment angle in the polar region. Based on a large misalignment angle, nonlinear navigation error equations, which are the UKF dynamic models, are derived under grid frames. This paper chooses the velocity plus attitude matching method as the TA matching method and errors of velocity and attitude as observations. The misalignment angle can be estimated by the designed UKF. The simulation results have demonstrated that the polar TA algorithm can be effective in improving the TA accuracy, especially when large misalignment angles occur.

Due to the lever-arm effect and flexural deformation in the practical application of transfer alignment (TA), the TA performance is decreased. The existing polar TA algorithm only compensates a fixed lever-arm without considering the dynamic lever-arm caused by flexural deformation; traditional non-polar TA algorithms also have some limitations. Thus, the performance of existing compensation algorithms is unsatisfactory. In this paper, a modified compensation algorithm of the lever-arm effect and flexural deformation is proposed to promote the accuracy and speed of the polar TA. On the basis of a dynamic lever-arm model and a noise compensation method for flexural deformation, polar TA equations are derived in grid frames. Based on the velocity-plus-attitude matching method, the filter models of polar TA are designed. An adaptive Kalman filter (AKF) is improved to promote the robustness and accuracy of the system, and then applied to the estimation of the misalignment angles. Simulation and experiment results have demonstrated that the modified compensation algorithm based on the improved AKF for polar TA can effectively compensate the lever-arm effect and flexural deformation, and then improve the accuracy and speed of TA in the polar region.

The conventional initial alignment algorithms are invalid in the polar region. This is caused by the rapid convergence of the Earth meridians in the high-latitude areas. However, the initial alignment algorithms are important for the accurate navigation of Unmanned Underwater Vehicles. The polar transversal initial alignment algorithm is proposed to overcome this problem. In the polar transversal initial alignment algorithm, the transversal geographic frame is chosen as the navigation frame. The polar region in the conventional frames is equivalent to the equatorial region in the transversal frames. Therefore, the polar transversal initial can be effectively applied in the polar region. According to the complex environment in the polar region, a large misalignment angle is considered in this paper. Based on the large misalignment angle condition, the non-linear dynamics models are established. In addition, the simplified unscented Kalman filter (UKF) is chosen to realize the data fusion. Two comparison simulations and an experiment are performed to verify the performance of the proposed algorithm. The simulation and experiment results indicate the validity of the proposed algorithm, especially when large misalignment angles occur.