Paper Info
Title
DVL-Aided SINS In-Motion Alignment Filter Based on a Novel Nonlinear Attitude Error Model.
Abstract
A novel nonlinear attitude error model based on square root cubature information filter (SR-CIF) is proposed aiming to speed up the convergence rate of DVL-aided strapdown inertial navigation system (SINS) in-motion initial alignment for autonomous underwater vehicle (AUV) when both large initial heading error and large initial level attitude errors exist The new nonlinear attitude error model and measurement model are applicable for initial alignment after a short-time coarse alignment with large attitude errors exist. The SR-CIF embeds the whole iterative process into the data structure framework of the information filtering, replacing the covariance matrix in the square root cubature Kalman filter (SR-CKF) with an information matrix which simplifies the filter initialization. The square root technology ensures the symmetry and positive definiteness of the information matrix with enhanced stability of the filter. The simulation and experimental results indicate that the proposed DVL-aided alignment filter is effective with large initial attitude errors. The rate of convergence and estimation accuracy of the SR-CIF is higher than that of the conventional SR-CKF with large attitude misalignments.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2916182
IEEE ACCESS
Keywords
Field
DocType
DVL-aided SINS alignment,large initial attitude errors,nonlinear attitude error model,square root cubature information filter
Inertial navigation system,Computer science,Control theory,Filter (signal processing),Rate of convergence,Fisher information,Initialization,Covariance matrix,Square root,Information filtering system,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Lu Zhang116340.09
Wenqi Wu28915.21
Maosong Wang3172.32
Yan Guo47712.73