Attitude Tracking and Location Algorithm of Drill Bit for Underwater Mud-Penetrator

Abstract:

This paper proposed a navigation algorithm based on indirect square root kalman filter. On the basis of rigorous argument about the sensor measurement error, we established state error equation based on sensor random walk model and deduced the relationship between state error and steady-state component of acceleration and angular velocity. Considered the divergence of kalman filter in the update stage, we used square root kalman filter to calculate the true value of state error which can be used to correct the predictive value of state. In order to provide acceleration, angular velocity and velocity for the proposed algorithm, we installed an imu7200 within the drill bit and mounted an encoder on the wheel of the delivery tube device. Marine experiments in the east china sea show that the proposed algorithm can implement accurate location and attitude tracking of drill bit.

• Periodical: Applied Mechanics and Materials (Volume 203)
• Pages: 395-400
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.203.395
• Online since: October 2012
• Authors: Ke Yang, Tong Ge, Xu Yang Wang
• Keywords: Indirect Square Root Kalman Filter, Random Walk Model, State Error, Steady-State Component

References

[1] Jun Ming Wu: submitted to Journal of Shanghai Dianji University (2005).

[2] Bao Fu Xu, Yun Fei Le and Wei Xing Chen: submitted to Journal of Hydraulics Pneumatics & Seals (2002).

[3] Rui Wang, Bao Xiong Wang and Jian Kang: submitted to Journal of Exploration Engineering (2009).

[4] Wei Liu, Xu Hui Jie and Sheng Yi Li: submitted to Journal of Beijing University of Aeronautics and Astronautics (2005).

[5] H.K. Lee, J.G. Lee and G.I. Jee: submitted to Journal of Guidance, Control and Dynamics (1994).

[6] Hong Liang Zhang, Guang Hong Gong and Jiang Hong Wang: submitted to Journal of System Simulation (2006).

[7] Information on http: /www. lib. sjtu. edu. cn.