UUV offensive mine-laying marine environmental risk assessment and scheme selection

• Published in: Zhongguo Jianchuan Yanjiu Vol. 16; no. Supp1; pp. 31 - 39
• Main Authors: Xifan YIN, Xin LI, Ren Zhang, Yongqiang ZHAN, Xianghong ZHAO
• Format: Journal Article
• Language: English
• Published: Editorial Office of Chinese Journal of Ship Research 01.12.2021
• Subjects: combined weight; marine environmental risk assessment; scheme selection; set pair analysis (spa); topsis; unmanned underwater vehicle (uuv) offensive mine-laying
• ISSN: 1673-3185
• DOI: 10.19693/j.issn.1673-3185.01974

ObjectivesThis study constructs a quantitative assessment model of the impact of the marine environment on the offensive mine-laying operational performance of unmanned underwater vehicles (UUV), and draws quantitative evaluation conclusions.MethodsFirst, the attributes of offensive mine-laying marine environment assessment are researched and the optimal model of the TOPSIS and set pair analysis (SPA) method are proposed on the basis of the combined weight of the fuzzy analytic hierarchy process (FAHP) and entropy weight method (EWM). The current situation of UUV deployment and its impact on the marine environment are then analyzed, and the risk indexes of the marine environment on the offensive mine-laying performance of UUVs are constructed with reference to the main evaluation indexes of the operational performance of traditional and unmanned offensive mine-laying. Finally, according to the existing research results on the impact of the marine environment on UUV systems, a quantitative model of the risk indicators is completed.ResultsThe feasibility of the method and model presented in this paper is verified through a simulation experiment that optimizes the marine environmental risk scheme of the determined UUV offensive mine-laying.conclusionsIt is more effective to disassemble the marine environmental risk indications in the offensive mine-laying stage, and more scientific to construct a quantitative model of marine environmental risk indications. The dynamic preference coefficient of the combined weight takes into account both the authority of decision-making and objectivity of data, and the influence of the same and opposite factors on scheme selection is considered. Finally, the feasibility of the algorithm is verified by the simulation results.