Hostname: page-component-848d4c4894-ndmmz Total loading time: 0 Render date: 2024-06-13T10:07:28.626Z Has data issue: false hasContentIssue false

Terrain Correlation Correction Method for AUV Seabed Terrain Mapping

Published online by Cambridge University Press:  05 April 2017

Ye Li
Affiliation:
(Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China)
Teng Ma*
Affiliation:
(Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China)
Rupeng Wang
Affiliation:
(Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China)
Pengyun Chen
Affiliation:
(College of Mechatronic Engineering, North University of China)
Qiang Zhang
Affiliation:
(Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China)

Abstract

A method is proposed for improving the accuracy and self-consistency of bathymetric maps built using an Autonomous Underwater Vehicle (AUV) to create precise prior maps for Terrain-Aided Navigation (TAN), when the Global Positioning System (GPS) or another precise location method is unavailable. This method consists of front-end and back-end. For the front-end, the AUV predicts the measurement of the bathymetry system through Terrain Elevation Measurement Extrapolation Estimation (TEMEE) and calculates the likelihood function using real measurements. After the final Inertial Navigation System (INS) error is obtained by communicating with sensor nodes, the process enters the back-end. A Terrain Correlation Correction Method (TCCM) and an Improved Terrain Correlation Correction Method (ITCCM) are proposed to solve the gradual distribution of the final INS error to each point on a path, and the accuracy of ITCCM was confirmed experimentally. Finally, a TAN simulation experiment was conducted to prove the importance and necessity of map correction using ITCCM. ITCCM was proven to be an effective and important method for correcting maps built using an AUV.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Bar-Shalom, Y. and Chen, H. (2004). Multi-sensor track-to-track association for tracks with dependent errors. IEEE Conference on Decision & Control, Vol.3, 26742679.Google Scholar
Barkby, S., Williams, S., Pizarro, O. and Jakuba, M. (2009). Incorporating prior maps with Bathymetric Distributed Particle SLAM for improved AUV navigation and mapping. Oceans Bremen, IEEE, 17.Google Scholar
Bellingham, J.G., Zhang, Y., Kerwin, J.E., Erikson, J., Hobson, B. and Kieft, B. (2010). Efficient propulsion for the Tethys long-range autonomous underwater vehicle. Autonomous Underwater Vehicles, IEEE/OES, Riga, Latvia, 17).CrossRefGoogle Scholar
Caiti, A., Corato, F.D., Fenucci, D. and Allotta, B. (2014). Experimental results with a mixed USBL/LBL system for AUV navigation. Underwater Communications and Networking, Sestri Levante, IEEE, 14.Google Scholar
Chen, P., Li, Y., Su, Y., Chen, X. and Jiang, Y. (2015). Review of AUV underwater terrain matching navigation. Journal of Navigation, 68(6), 11551172.Google Scholar
Cox, R. and Wei, S. (1995). Advances in the state of the art for AUV inertial sensors and navigation systems. IEEE Journal of Oceanic Engineering, 20(4), 361366.Google Scholar
Donovan, G.T. (2012). Position error correction for an autonomous underwater vehicle inertial navigation system (ins) using a particle filter. IEEE Journal of Oceanic Engineering, 37(3), 431445.Google Scholar
Golfarelli, M., Maio, D. and Rizzi, S. (1998) Elastic correction of dead-reckoning errors in map building. Proceedings of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications, Victoria, Canada, 905911.Google Scholar
Groves, P.D., Handley, R.J. and Runnalls, A.R. (2006). Optimising the integration of terrain referenced navigation with INS and GPS. Journal of Navigation, 59, 7189.CrossRefGoogle Scholar
Gutmann, J.S. and Konolige, K. (1999). Incremental mapping of large cyclic environments. IEEE International Symposium on Computational Intelligence in Robotics and Automation, Cira 99, Monterey, California, 318325.Google Scholar
Lu, F. and Milios, E. (1997). Globally consistent range scan alignment for environment mapping. Autonomous Robots, 4(4), 333349.Google Scholar
Matthies, L. (2012). Fully self-contained vision-aided navigation and landing of a micro air vehicle independent from external sensor inputs. Proceedings of International Society for Optical Engineering, 8387, 83870Q–83870Q-10.Google Scholar
Mok, S.H., Bang, H., Kwon, J. and Yu, M. (2013). Terrain referenced navigation for autonomous underwater vehicles. Journal of Institute of Control, 19(8), 702708.Google Scholar
Olson, E., Leonard, J. and Teller, S. (2013). Fast iterative alignment of pose graphs with poor initial estimates. IEEE International Conference on Robotics & Automation, Karlsruhe, Germany, 22622269.Google Scholar
Paull, L., Saeedi, S., Seto, M. and Li, H. (2014). AUV navigation and localization: a review. IEEE Journal of Oceanic Engineering, 39(1), 131149.Google Scholar
Song, Z., Bian, H. and Zielinski, A. (2015). Underwater terrain-aided navigation based on multibeam bathymetric sonar images. Journal of Marine Science & Application, 14(4), 425433.Google Scholar
Zandi, R., Kamarei, M. and Amiri, H. (2015). Distributed estimation of sensors position in underwater wireless sensor network. International Journal of Electronics, 103(5).Google Scholar
Zhang, K., Li, Y., Zhao, J. and Rizos, C. (2014). A study of underwater terrain navigation based on the robust matching method. Journal of Navigation, 67(4), 569578.Google Scholar
Zhang, T., Xu, X. and Xu, S. (2015). Method of establishing an underwater digital elevation terrain based on kriging interpolation. Measurement, 63, 287298.Google Scholar