Strong Tracking Filter Based on Extended Kalman Filter for Data Processing of Underwater Vehicle

Abstract:

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A strong tracking filter based on suboptimal fading extended Kalman filter was proposed to ensure the perception for the motion state of underwater vehicles accurate in the paper. For the uncertainty of nonlinear system model, the strong tracking filter theory was introduced, orthogonality principle was put forward. Then suboptimal fading factor was pulled in, and extended Kalman filter for nonlinear system was established. The strong tracking filter was applied to data processing of underwater vehicle, and results indicate that it can effectively improve the accuracy and robustness of underwater navigation information.

Info:

Periodical:

Advanced Materials Research (Volumes 219-220)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

569-573

Citation:

Y. Li et al., "Strong Tracking Filter Based on Extended Kalman Filter for Data Processing of Underwater Vehicle", Advanced Materials Research, Vols. 219-220, pp. 569-573, 2011

Online since:

March 2011

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Price:

$38.00

[1] P.A. Miller and J.A. Farrell: Autonomous Underwater Vehicle Navigation. IEEE Journal of Oceanic Engineering, Vol. 35(3) (2010), pp.663-678.

[2] Z.L. Deng: Optimal estimation theory and its applications— modeling, simulation, information fusion estimation (Harbin Institute of Technology Press, Harbin 2005).

[3] J.C. Liu and Y.R. Xu: A filtering method with neural network for underwater vehicle. Ocean Engineering, Vol. 20(3) (2002), pp.34-38.

[4] H. Zhu and J. Mo: Information fusion technology for underwater navigation (National Defense Industry Press, Beijing 2002).

[5] M.Y. Fu, Z.H. Deng and J.W. Zhang: Kalman Filter Theory and Application in Navigation System (Science Press, Beijing 2003).

[6] V.T. Dang: An Adaptive Kalman Filter for Radar Tracking Application. Symposium Proceedings, Vol. 9 (2008), pp.261-264.

[7] G. Welch and G. Bishop: An Introduction to the Kalman Filter. UNCChapel Hill, TR 95-04 (2006).

[8] L. Wan, L. Li, J.C. Liu and Y.R. Xu: Navigation Algorithm Based on Dead Reckoning of Automatic Underwater Vehicle. Shipbuilding of China, Vol. 45(4) (2004), pp.77-82.

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