Method of on-call submarine searching for surface ship formation based on hidden Markov model
<b>[Objectives]</b> In order to improve the successful probability of searching for target submarines and to make the operation of the surface ship formation more effectively,the problem about the path planning for the on-call submarine searching for ships is studied.<b>[Methods]&l...
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Editorial Office of Chinese Journal of Ship Research
2019-12-01
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doaj-b725aa64de3f4df4a8acc8aba9c442352020-11-25T02:20:06ZengEditorial Office of Chinese Journal of Ship ResearchZhongguo Jianchuan Yanjiu1673-31851673-31852019-12-0114619220010.19693/j.issn.1673-3185.01507201906024Method of on-call submarine searching for surface ship formation based on hidden Markov modelBian Dapeng0Yu Shanshan1Zhang Shi2Yu Minghui3Wang Yun4Wuhan Second Military Representative Office, Naval Armament Department of PLAN, Wuhan 430064, ChinaSchool of Automation, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Automation, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Automation, Huazhong University of Science and Technology, Wuhan 430074, ChinaChina Ship Development and Design Center, Wuhan 430064, China<b>[Objectives]</b> In order to improve the successful probability of searching for target submarines and to make the operation of the surface ship formation more effectively,the problem about the path planning for the on-call submarine searching for ships is studied.<b>[Methods]</b> Firstly, an on-call submarine searching model of surface ships was constructed based on the Hidden Markov Model(HMM). A two-stage heuristic method was designed to maximize the probability of searching for submarine search expectation. The problem of local optimum was avoided by using evolutionary algorithm(EA)to cross and mutate the individuals in the population,and a comparison with conventional searching methods was made. Then, the effects of different segmentation methods on path optimization were studied experimentally.<b>[Results]</b> The simulation results of single-ship and multi-ship searching for submarines show that the method adopted in this paper can obtain the maximum submarine search expectation and the optimal searching path. The segmentation times experiment show that a reasonable re-division of the search area is beneficial to find a better searching path.<b>[Conclusions]</b> This model can find an optimal path for submarine search and improve the searching efficiency of the surface ship formation.http://www.ship-research.com/EN/Y2019/V14/I6/192hidden markov model(hmm)on-call submarine searchingevolutionary algorithm(ea)path optimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bian Dapeng Yu Shanshan Zhang Shi Yu Minghui Wang Yun |
spellingShingle |
Bian Dapeng Yu Shanshan Zhang Shi Yu Minghui Wang Yun Method of on-call submarine searching for surface ship formation based on hidden Markov model Zhongguo Jianchuan Yanjiu hidden markov model(hmm) on-call submarine searching evolutionary algorithm(ea) path optimization |
author_facet |
Bian Dapeng Yu Shanshan Zhang Shi Yu Minghui Wang Yun |
author_sort |
Bian Dapeng |
title |
Method of on-call submarine searching for surface ship formation based on hidden Markov model |
title_short |
Method of on-call submarine searching for surface ship formation based on hidden Markov model |
title_full |
Method of on-call submarine searching for surface ship formation based on hidden Markov model |
title_fullStr |
Method of on-call submarine searching for surface ship formation based on hidden Markov model |
title_full_unstemmed |
Method of on-call submarine searching for surface ship formation based on hidden Markov model |
title_sort |
method of on-call submarine searching for surface ship formation based on hidden markov model |
publisher |
Editorial Office of Chinese Journal of Ship Research |
series |
Zhongguo Jianchuan Yanjiu |
issn |
1673-3185 1673-3185 |
publishDate |
2019-12-01 |
description |
<b>[Objectives]</b> In order to improve the successful probability of searching for target submarines and to make the operation of the surface ship formation more effectively,the problem about the path planning for the on-call submarine searching for ships is studied.<b>[Methods]</b> Firstly, an on-call submarine searching model of surface ships was constructed based on the Hidden Markov Model(HMM). A two-stage heuristic method was designed to maximize the probability of searching for submarine search expectation. The problem of local optimum was avoided by using evolutionary algorithm(EA)to cross and mutate the individuals in the population,and a comparison with conventional searching methods was made. Then, the effects of different segmentation methods on path optimization were studied experimentally.<b>[Results]</b> The simulation results of single-ship and multi-ship searching for submarines show that the method adopted in this paper can obtain the maximum submarine search expectation and the optimal searching path. The segmentation times experiment show that a reasonable re-division of the search area is beneficial to find a better searching path.<b>[Conclusions]</b> This model can find an optimal path for submarine search and improve the searching efficiency of the surface ship formation. |
topic |
hidden markov model(hmm) on-call submarine searching evolutionary algorithm(ea) path optimization |
url |
http://www.ship-research.com/EN/Y2019/V14/I6/192 |
work_keys_str_mv |
AT biandapeng methodofoncallsubmarinesearchingforsurfaceshipformationbasedonhiddenmarkovmodel AT yushanshan methodofoncallsubmarinesearchingforsurfaceshipformationbasedonhiddenmarkovmodel AT zhangshi methodofoncallsubmarinesearchingforsurfaceshipformationbasedonhiddenmarkovmodel AT yuminghui methodofoncallsubmarinesearchingforsurfaceshipformationbasedonhiddenmarkovmodel AT wangyun methodofoncallsubmarinesearchingforsurfaceshipformationbasedonhiddenmarkovmodel |
_version_ |
1724873543187955712 |