Strong tracking adaptive Kalman filters for underwater vehicle dead reckoning

Abstract

To impove underwater vehicle dead reckoning, a developed strong tracking adaptive kalman filter is proposed. The filter is improved with an additional adaptive factor and an estimator of measurement noise covariance. Since the magnitude of fading factor is changed adaptively, the tracking ability of the filter is still enhanced in low velocity condition of underwater vehicles. The results of simulation tests prove the presented filter effective.

Keywords

dead reckoning / underwater vehicle / strong tracking kalman filter / measurement noise

References

[1] Feng Z., Liu J., Liu K. Dead reckoning method for autonomous navigation of autonomous underwater vehicle[J]. Robot, 2005, 27(2): 168-172

[2] LI Lu, WAN Lei. Applied navigation system of “SY-1” small AUV[A]. Proceedings of 13th International Symposium on Unmanned Untethered Submersible Technology[C]. New Hampshire, 2003.

[3] Mo J., Zhu H. Data fusion between GPS and calculation of position based ocean database[J]. Computer Simulation, 2002, 19(5): 25-29

[4] XIAO Q, RAO M, YING Y and SUN Y. A new state estimation algorithm-adaptive fading kalman filter[A]. Proceedings of the 31st conference on decision and control[C]. Tucson, USA, 1992.

[5] Fang J., Wan D., Wu Q., Shen G. A new kinematic filtering method of GPS positioning for moving vehicle[J]. Journal of Chinese Intertial Technology, 1997, 5(2): 4-10