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Underwater Terrain Positioning Method Using Maximum a Posteriori Estimation and PCNN Model

  • Pengyun Chen (a1), Pengfei Zhang (a1), Teng Ma (a2), Peng Shen (a3), Ye Li (a2), Rupeng Wang (a2), Yue Han (a4) and Lizhou Li (a1)...

Abstract

Conventional underwater navigation and positioning methods for Autonomous Underwater Vehicles (AUVs) either require the installation of acoustic arrays, which make AUVs less independent, or result in cumulative errors. This paper proposes an Underwater Terrain Positioning Method (UTPM) using Maximum a Posteriori (MAP) estimation and a Pulse Coupled Neural Network (PCNN) model for highly accurate navigation by AUVs. The PCNN model is used as a secondary discriminant to effectively identify pseudo-anchor points in flat terrain feature areas and to find the true positioning point, which significantly improves the matching positioning accuracy in these areas. Simulation results show that the proposed method effectively corrects Inertial Navigation System (INS) cumulative errors and has high matching positioning accuracy, which satisfy the requirements of AUV underwater navigation and positioning.

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Bergman, N. and Ljung, L. (2009). Point-mass filter and Cramer-Rao bound for terrain-aided navigation. Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking. Wiley-IEEE Press, 850855.
Chang, Q., Yang, D. K., Kou, Y. H. and Zhang, Q. S. (2005). Vehicle Navigation Positioning Method and Application. Mechanical Industry Press.
Chen, P. Y., Li, Y., Su, Y., Chen, X. and Jiang, Y. (2015). Review of AUV underwater terrain matching navigation. The Journal of Navigation, 68(6), 11551172.
Chen, X. L. (2013). A study on underwater terrain matching aided navigation technology of AUV. PhD Thesis, Harbin Engineering University.
Claus, B. and Bachmayer, R. (2015). Terrain-aided navigation for an underwater glider. Journal of Field Robotics, 32(1), 935951.
Ding, J. L. and Xiao, J. (2014). Design of adaptive cubature Kalman filter based on maximum a posteriori estimation. Control and Decision, 29(2), 327334.
Eckhorn, R., Reitboeck, H. J., Arndt, M. and Dicke, P. (1990). Feature linking via synchronization among distributed assemblies: Simulation of results from cat cortex. Neural Computation, 2, 293307.
Geisser, S. (1992). Introduction to Fisher (1922) On the mathematical foundations of theoretical statistics. In: Kotz, S., Johnson, N.L. eds., Breakthroughs in Statistics. Springer Series in Statistics (Perspectives in Statistics). New York: Springer, 110
GeoAcoustics Limited. (2007). GeoSwath Plus Operation Manual, GeoAcoustics Limited. UK.
Hagen, O. K. and Anonsen, K. B. (2014). Using terrain navigation to improve marine vessel navigation systems. Marine Technology Society Journal, 48(2), 4558.
Hagen, O. K., Anonsen, K. B. and Saebo, T. O. (2012). Low-altitude terrain navigation for underwater vehicles integration of an interferometric side scan sonar improves terrain navigation in low-altitude scenarios. Sea Technology, 53(6), 1013.
Ji, D. and Liu, J. (2010). Ray theory application in long baseline system. China Ocean Engineering, 24(1), 199206.
Lee, H. (2016). Optimization of computation efficiency in underwater acoustic navigation system. The Journal of the Acoustical Society of America, 139(4), 19091913.
Li, Y., Chen, P. Y. and Dong, Z. P. (2011). Sensor simulation of underwater terrain matching based on sea chart. Communications in Computer and Information Science, 216, 8994.
Li, Y., Ma, T., Chen, P. Y., Jiang, Y. Q., Wang, R. and Zhang, Q. (2017). Autonomous underwater vehicle optimal path planning method for seabed terrain matching navigation. Ocean Engineering, 133(133), 107115.
Lindblad, T. and Kinser, J. (2013). Image Processing using pulse-coupled neural networks: Applications in Python. Springer Science and Business Media.
Mohammed, M. M., Badr, A. and Abdelhalim, M. B. (2015). Image classification and retrieval using optimized pulse-coupled neural network. Expert Systems with Applications, 42(2015), 49274936.
Morgado, M., Oliveira, P. and Silvestre, C. (2013). Tightly coupled ultrashort baseline and inertial navigation system for underwater vehicles: An experimental validation. Journal of Field Robotics, 30(1), 142170.
Nordlund, P. J. and Gustafsson, F. (2010). marginalized particle filter for accurate and reliable terrain-aided navigation. IEEE Transactions on Aerospace & Electronic Systems, 45(4), 13851399.
Nygren, I. (2005). Terrain Navigation for Underwater Vehicles. PhD Thesis of the Royal Institute of Technology.
Nygren, I. (2008). Robust and efficient terrain navigation of underwater vehicles. Proceedings of IEEE/ION Position, Location and Navigation Symposium, Monterey, CA, USA, 923932.
Pan, X. H. and Zhao, L. (2015). Application of an unscented Kalman filter algorithm in the seabed terrain aided navigation. Applied Science and Technology, 42(1), 4952.
Paull, L., Saeedi, S. and Seto, M. (2014). AUV navigation and localization: A review. IEEE Journal of Oceanic Engineering, 39(1), 131149.
Peng, D. D., Zhou, T., Li, H. S. and Zhang, W. Y. (2016). Terrain aided navigation for underwater vehicles using maximum likelihood method. Proceedings of 2016 IEEE/OES China Ocean Acoustics Symposium, Harbin, China, 16.
Teixeira, F. C., Quintas, J., Maurya, P. and Pascoal, A. (2017). Robust particle filter formulations with application to terrain-aided navigation. International Journal of Adaptive Control and Signal Processing, 31(4), 608651.
Wang, H., Yan, L., Qian, X. and Zhu, M. (2007). Integration terrain match algorithm based on terrain entropy and terrain variance entropy. Computer Technology and Development, 17(9), 2527.
Xie, Y.R. (2005). Terrain Aided Navigation. MSc Thesis, the Royal Institute of Technology.
Xing, T. H. (2004). The research of terrain-aided underwater navigation. MSc Thesis, Northwest Polytechnical University.
Xu, Y. R., Pang, Y. J., Gan, Y. and Sun, Y. S. (2006). AUV—State of the art and prospect. CAAI Transactions on Intelligent Systems, 1(1), 916.
Yan, Z. P., Peng, S. P., Zhou, J. J., Xu, J. and Jia, H. (2010). Research on an improved dead reckoning for AUV navigation. Proceedings of 2010 Chinese Control and Decision Conference, Xuzhou, Jiangsu, China, 17941798.
Yao, Y. B., Hu, M. X. and Xu, C. Q. (2016). Positioning accuracy analysis of GPS/BDS/GLONASS network RTK based on DREAMNET. Acta Geodaeticaet Cartographica Sinica, 45(9), 10091018.
Zhao, L., Gao, N., Huang, B., Wang, Q. and Zhou, J. (2015). A Novel Terrain-Aided Navigation Algorithm Combined with the TERCOM Algorithm and Particle Filter. IEEE Sensors Journal, 15(2), 11241131.

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