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http://dx.doi.org/10.9766/KIMST.2022.25.1.072

Online Sonobuoy Deployment Method with Bayesian Optimization for Estimating Location of Submarines  

Kim, Dooyoung (Department of Cyber Science, Republic of Korea Naval Academy)
Publication Information
Journal of the Korea Institute of Military Science and Technology / v.25, no.1, 2022 , pp. 72-81 More about this Journal
Abstract
Maritime patrol aircraft is an efficient solution for detecting submarines at sea. The aircraft can only detect submarines by sonobuoy, but the number of buoy is limited. In this paper, we present the online sonobuoy deployment method for estimating the location of submarines. We use Gaussian process regression to estimate the submarine existence probability map, and Bayesian optimization to decide the next best position of sonobuoy. Further, we show the performance of the proposed method by simulation.
Keywords
Sensor Deployment; Bayesian Optimization; Reinforcement Learning;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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