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Research Articles

Automatic Recognition of Geomagnetic Suitability Areas for Path Planning of Autonomous Underwater Vehicle

ORCID Icon, , , , ORCID Icon &
Pages 287-305 | Received 16 Jun 2020, Accepted 16 Mar 2021, Published online: 16 Apr 2021

References

  • Cao, X., D. Zhu, and S. Yang. 2015. Multi-AUV target searching under ocean current based on ppso and velocity synthesis algorithm. Underwater Technology 33 (1):31–9.
  • Chong, Y. 2017. Research on the Key Technologies of Underwater Geomagnetism Aided Inertial Navigation. Master's Thesis, Information Engineering University, Zhengzhou, China.
  • Cui, R., Y. Li, and W. Yan. 2016. Mutual information-based multi-AUV path planning for scalar field sampling using multidimensional RRT*. IEEE Transactions on Systems, Man, and Cybernetics: Systems 46 (7):993–1004.
  • Edward Jackson, J. 2003. A user’s guide to principal components. Hoboken, America: Wiley Series in Probability and Statistics.
  • Goldenberg, F. 2006. Geomagnetic navigation beyond the magnetic compass. In Proceedings of the IEEE/ION Position, Location, and Navigation Symposium, Coronado, CA, USA, 25-27 April 684–94.
  • Hu, X. 2013. Technologies on underwater geomagnetic field navigation. Beijing, China: National Defense Industry Press. ISBN 9787118089677.
  • Ji, D., J. Liu, and R. Zheng. 2013. Acoustic theory application in ultra short baseline system for tracking AUV. Marine Geodesy 36:428–35.
  • Li, H., M. Liu, K. Liu, and F. Zhang. 2017. A study on the model of detecting the variation of geomagnetic intensity based on an adapted motion strategy. Sensors 18 (2):39.
  • Liu, H., and J. Qiu. 2015. Improved adaptive genetic algorithm in optimal layout of leather rectangular parts. Advances in Natural Science 8:20–6.
  • Liu, Y., J. Zhou, and Z. Ge. 2010. A projecting pursuit-based selection method for matching region in geomagnetism navigation. Journal of Astronautics 31:2677–82.
  • Li, Z., W. Zheng, J. Fang, and F. Wu. 2019. Optimizing Suitability Area of Underwater Gravity Matching Navigation Based on a New Principal Component Weighted Average Normalization Method. Chinese Journal of Geophysics 62:3269–78.
  • Meyer, B., A. Chulliat, and R. Saltus. 2017. Derivation and Error Analysis of the Earth Magnetic Anomaly Grid at 2 Arc-Minute Resolution Version 3 (EMAG2v3). Geochemistry, Geophysics, Geosystems 18 (12):4522–37.
  • Paull, L., S. Saeedi, M. Seto, and H. Li. 2014. AUV Navigation and Localization: A Review. IEEE Journal of Oceanic Engineering 39 (1):131–49.
  • Shen, L., Y. Bu, X. Xu, and L. Pan. 2010. Research on Matching-area Suitability for Scene Matching Aided Navigation. Acta Aeronautica Et Astronautica Sinica 31:553–63.
  • Srinivas, M., and L. Patnaik. 1994. Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms. IEEE Transactions on Systems, Man, and Cybernetics 24 (4):656–67.
  • Sun, G., L. Qin, Z. Hou, X. Jing, F. He, F. Tan, S. Zhang, and S. Zhang. 2019. Feasibility Analysis for Acquiring Visibility Based on Lidar Signal Using Genetic Algorithm-Optimized Back Propagation Algorithm. Chinese Physics B 28 (2):024213–87.
  • Wang, C. 2018. Geomagnetic Navigation Matching Area Selection Based on PCA and GA-BP Neural Network. Electronics Optics&Control 25:110–4.
  • Wang, P., J. Cao, and X. Hu. 2017. Research on matching suitability for underwater geomagnetic navigation; Beijing, China: National Defense Industry Press. ISBN 978118102741
  • Wang, P., X. Hu, and M. Wu. 2014a. Matching Suitability Analysis for Geomagnetic Aided Navigation Based on an Intelligent Classification Metho. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 228 (2):271–83.
  • Wang, P., X. Hu, and M. Wu. 2014b. Route Planning of Geomagnetic Aided Navigation for Vehicle under Matching Suitability Constraints. Applied Mechanics and Materials 454:39–42.
  • Wang, L., L. Yu, N. Qiao, and D. Sun. 2016. Analysis and simulation of geomagnetic map suitability based on vague set. Journal of Navigation 69:1114–24.
  • Wang, J., B. Zhang, B. Wu, and Y. Guo. 2020. Research on adaptability evaluation of underground geomagnetic positioning based on BP neural network with contribution factor. Journal of Hefei University of Technology (Natural Science) 43:1668–75.
  • Xiao, J., X. Qi, X. Duan, and J. Wang. 2017. Direction Navigability Analysis for Geomagnetic Navigation Based on Parallel Convolutional Neural Networks. Journal of Chinese Inertial Technology 25:349–55.
  • Xiao, J., X. Duan, X. Qi, and J. Zhong. 2016. Research on Suitable Matching Area in Geomagnetic Navigation. In 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics, Hangzhou, China, 1513–1517.
  • Zhang, L., S. Li, and X. Jia. 2016. A Method for Automatically Selecting Aids to Navigation Based on their Spatial Influence Domains. Marine Geodesy 43:189–212.
  • Zhang, H., L. Yang, and M. Li. 2019. A Novel Comprehensive Model of Suitability Analysis for Matching Area in Underwater Geomagnetic Aided Inertial Navigation. Mathematical Problems in Engineering 2019:1–11.
  • Zhang, K., J. Zhao, C. Shi, and H. Zhang. 2013. Study on Classification of Matching Area of Underwater Topography Based on BP Neural Network. Geomatics and Information Science of Wuhan University 38:56–9.
  • Zhang, K., J. Zhao, and Q. Wang. 2013. Study on Recognition and Classification of Appropriate Matching Area for Underwater Navigation Based on SVM. Journal Geodesy and Geodynamics 33:72–7.
  • Zhao, J., S. Wang, and A. Wang. 2011. Study on the Selection of the Geomagnetic Adaptable Matching Area Based on the Geomagnetic Co-occurrence Matrix. Geomatics and Information Science of Wuhan University 36:446–9.
  • Zheng, H., H. Wang, L. Wu, H. Chai, and Y. Wang. 2013. Simulation Research on Gravity-Geomagnetism Combined Aided Underwater Navigation. Journal of Navigation 66:83–98.
  • Zhou, X., S. Li, J. Yang, and L. Zhang. 2008. Selective Criteria of Characteristic Area on Geomagnetic Map. Journal of Chinese Inertial Technology 16:694–8.
  • Zitova, B., and J. Flusser. 2003. Image Registration Methods: A Survey. Image and Vision Computing 21 (11):977–1000.

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