Title :
Strapdown inertial navigation system alignment based on marginalised unscented kalman filter
Author :
Lubin Chang ; Baiqing Hu ; An Li ; Fangjun Qin
Author_Institution :
Dept. of Navig. Eng., Naval Univ. of Eng., Wuhan, China
Abstract :
This study concerns the strapdown inertial navigation system (SINS) initial alignment under marine mooring condition with large initial error. The ten-dimensional state initial alignment error functions of the SINS with inclusion of non-linear characteristics have been derived. It is pointed out for the first time that the non-linear functions are applied to only a subset of the elements of the state vector, that is, the velocities error and the misalignment angles. Then a computationally efficient refinement of the unscented transformation (UT) called marginalised UT (MUT) is investigated in these special non-linear systems with a linear substructure. A performance comparison between the extended Kalman filter (EKF), the UT-based Kalman filter (UKF) and the MUT-based Kalman filter (MUKF) demonstrates that both the UKF and the MUKF can outperform the EKF and the MUKF and can achieve, if not better, at least a comparable performance to the UKF, at a significantly lower expense.
Keywords :
Kalman filters; inertial navigation; nonlinear filters; EKF; MUKF; MUT; SINS initial alignment; computationally efficient refinement; extended Kalman filter; linear substructure; marginalised UT; marginalised unscented Kalman filter; marine mooring condition; nonlinear characteristics; state vector; strapdown inertial navigation system alignment; strapdown inertial navigation system initial alignment; ten-dimensional state initial alignment error functions; unscented transformation; velocities error;
Journal_Title :
Science, Measurement & Technology, IET
DOI :
10.1049/iet-smt.2012.0071