Application of Modified Self-Adaptive Kalman Filter in Integrated Navigation System of Autonomous Underwater Vehicle

Abstract:

Owing to the complex operating environment of underwater vehicles, many uncertainties of sensors data, big noises of sensors , low precision and high rate of wild points of underwater acoustic sensors, data processing of motion sensors data for underwater vehicle navigation system becomes extremely important. The integrated navigation system of autonomous underwater vehicle based on dead-reckoning is introduced. An modified adaptive Kalman filter is adopted for underwater vehicle sensors information data processing. Experimental results show that the modified self-adaptive Kalman filter(SAKF) is effective, and can meet the underwater robots perform a variety of tasks in the navigation and positioning accuracy..

• Periodical: Applied Mechanics and Materials (Volume 79)
• Pages: 298-303
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.79.298
• Online since: July 2011
• Authors: Yu Shan Sun, Wen Jiang Li, Zai Bai Qin, Hong Li Chen, Ji Qing Li
• Keywords: Autonomous Underwater Vehicle (AUV), Dead-Reckoning, Integrated Navigation, Self-Adaptive Kalman Filter

References

[1] Zhu Hai, Mo Jun, Data fusion technology in underwater navigation. BeiJing: National Defence Industry Press. (2002).

[2] SUN Yushan, WANG Jianguo, WANG Bo. Research on the embedded navigation system of autonomous underwater vehicle based on th VxWorks. Journal of Basic Science and Engineering, 2009, 17(6): 899-909P.

[3] Lu Li, Lei Wan. Applied navigation system of SY-1, Small AUV. Proceedings of 13th International Symposium on Unmanned Untethered Submersible Technology, New Hampshire USA, August 24–27, (2003).

[4] Fu Zheng, Wang Shuman, Liu Bingjie. A overview of the development of adaptive Kalman filrering. Tactical Missile Technology, 2009, (6): 62-66P.

[5] Pang Yongjie, Sun Yushan, Gan Yong, Wan Lei. An integrated GPS/DR navigation system for AUV. Journal of Marine Science and Application. 2006, 5(4): 8-13P.

DOI: 10.1007/s11804-006-6023-z

[6] Yushan Sun, Xiao Liang, Lei Wan, Yongjie Pang. Design of the Embedded Navigation System of Autonomous Underwater Vehicle Based on the VxWorks. The Sixth IEEE International Conference on Control and Automation. Guangzhou, China, May 30-June 1, 2007：2919-2924P.

DOI: 10.1109/icca.2007.4376896

[7] Xu Jingshuo, Qin Yongyuan, Peng Rong. New method for selecting adaptive Kalman filter fading factor. Systems Engineering and Electronics, 2004, 26(11): 1552-1554P.