A New Method to Improve the Maneuver Capability of AUV Integrated Navigation Systems

The maneuver characteristic of the most commonly used AUV integrated navigation systems was investigated in this paper. After analyzing the error cause of conversional used Kalman filter of SINS/DVL integrated navigation systems in maneuver state, a novel method was proposed which is to use the output of complex navigation systems to revise the SINS in real-time, and an improved adaptive Kalman filter was discussed here to reach the seamless changing of the whole system. The measurement remnant method was introduced to judge whether the bearing change event happened or not. The whole design was aiming to reach the smooth transition between the different motion states and improve the maneuver capability of the AUV navigation system. The simulation results confirms the new approach could restrain the oscillation of Kalman filter in motion chang ing state and improve the accuracy of the AUV integrated navigation systems.

[1]  Dong Chaoyang An H_∞ Suboptimal Filter Target Tracking Algorithm With Acceleration Compensation , 2006 .

[2]  Wei Gao,et al.  Adaptive Extended Kalman Filtering for SINS/GPS Integrated Navigation Systems , 2009, 2009 International Joint Conference on Computational Sciences and Optimization.

[3]  Congwei Hu,et al.  Adaptive Kalman Filtering for DGPS Positioning , 2001 .

[4]  Guanrong Chen,et al.  Introduction to random signals and applied Kalman filtering, 2nd edn. Robert Grover Brown and Patrick Y. C. Hwang, Wiley, New York, 1992. ISBN 0‐471‐52573‐1, 512 pp., $62.95. , 1992 .

[5]  F. Gagnon,et al.  Fuzzy corrections in a GPS/INS hybrid navigation system , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[6]  Zhen Guo,et al.  Research on integrated navigation method for AUV , 2005 .

[7]  Honghai Liu,et al.  Navigation Technologies for Autonomous Underwater Vehicles , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[8]  T. Aoki,et al.  Accuracy Improvement of an Inertial Navigation System Brought about by the Rotational Motion , 2007, OCEANS 2007 - Europe.

[9]  Wu Chen,et al.  Adaptive Kalman Filtering for Vehicle Navigation , 2003 .

[10]  Hou Zengguang Application of an Adaptive Filter in Initial Alignment of Strapdown Inertial Navigation System with Large Misalignment Errors , 2008 .

[11]  Peter S. Maybeck,et al.  Multiple model adaptive estimation with filter spawning , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).