In order to improve the precision and convergence rate of SINS initial alignment with large misalignment angles, a novel nonlinear filtering method, referred as square root simplex unscented quadrature Kalman filter (SR-SUQKF) is introduced into the initial alignment in this paper. By using the method of simplex unscented transformation to select a few cubature points and combining with Gauss-Laguerre quadrature rule to improve the numerical accuracy, a new set of high order sampling points with determined number and weighting coefficient are constructed and used for filtering with a square-root extension to improve the numerical stability. By means of mathematical simulation and turntable experiment, the filter performance of square root cubature Kalman filter (SR-CKF) and SR-SUQKF using three points in one dimension in SINS/GPS initial alignment on a moving base with large misalignment angles is analyzed and compared. The results of both experiments show that under the condition of large misalignment angles, the three-point SR-SUQKF can perform the initial alignment with high accuracy and high speed, the alignment accuracy and convergence rate of the three-point SR-SUQKF are much better than that of SR-CKF. The SR-SUQKF can be effectively used for the initial alignment with large misalignment angles in SINS/GPS and would be able to overcome inherent disadvantages associated with the conventional nonlinear filters.
Novel nonlinear filter for sins initial alignment with large misalignment angles
01.04.2016
893360 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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