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Optimal Anti-submarine Search Path for UUV via an Adaptive Mutation Genetic Algorithm

  • Wenjun DingEmail author
  • Hui Cao
  • Hao Wu
  • Zhaoyong Mao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11741)

Abstract

Unmanned underwater vehicle (UUV) is significant equipment for underwater anti-submarine operation. In this paper, the optimal anti-submarine search path for UUV is investigated through an adaptive mutation genetic algorithm (AMGA). The AMGA utilizes three control factors to dominate the direction and amplitude of mutation adaptively and to improve the convergence speed. The mathematical programming model for UUV optimal search is established by maximizing cumulative detection probability (CDP). The enemy submarine is described as Markovian target, and the search radius and search width of the UUV are considered. Reasonable and efficient search paths are obtained under different conditions. The results indicate that the optimal path for UUV is effective and suggestive for anti-submarine search.

Keywords

Unmanned underwater vehicle (UUV) Anti-submarine search Optimal path Adaptive mutation genetic algorithm (AMGA) 

Notes

Acknowledgements

This research was partially supported by the National Natural Science Foundation of China (Grant Nos 61375055), the scholarship from China Scholarship Council (Grant No. 201506290080), the China Postdoctoral Science Foundation (Grant No. 2019M653652) and the Fundamental Research Funds for the Central Universities.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical EngineeringXi’an Jiaotong UniversityXi’anChina
  2. 2.Key Laboratory of Unmanned Underwater Vehicle Ministry of Industry and Information Technology, School of Marine Science and TechnologyNorthwestern Polytechnical UniversityXi’anChina
  3. 3.Department of Naval ArchitectureDalian University of TechnologyDalianChina

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