标题:Research on Unmanned Underwater Vehicle Threat Assessment
作者:Yao, Hongfei; Wang, Hongjian; Li, Yiming; Wang, Ying; Han, Chunsong
作者机构:[Yao, Hongfei; Wang, Hongjian; Li, Yiming; Wang, Ying] Harbin Engn Univ, Coll Automat, Harbin 150001, Heilongjiang, Peoples R China.; [Yao, Hongfei; 更多
通讯作者:Wang, Hongjian;Wang, HJ
通讯作者地址:[Wang, HJ]Harbin Engn Univ, Coll Automat, Harbin 150001, Heilongjiang, Peoples R China.
来源:IEEE ACCESS
出版年:2019
卷:7
页码:11387-11396
DOI:10.1109/ACCESS.2019.2891940
关键词:Dynamic Bayesian; threat assessment; unmanned underwater vehicle
摘要:The unmanned underwater vehicle (UUV) plays an ever increasing and important role in the modern marine environment. In particular, the tasks of underwater reconnaissance and surveillance, underwater mine hunting and anti-submarine warfare, all poses a serious and dangerous threat to humans. UUV has become the forerunning technology to accomplish such missions. In this paper, a method based on dynamic Bayesian network modeling was proposed to evaluate the UUV in an underwater threat situation. We divided the UUV threats into three categories: environmental factors, platform factors, and mission factors. Through each of these categories, we carried out factor extraction and set up the priori probability according to the characteristics. Setting up the static Bayesian network involved the addition of state transition probability and establishment of the model for assessing the dynamic Bayesian threat situation. By comparing the results of the static and dynamic Bayesian simulation, it was shown that the dynamic Bayesian is superior. Moreover, by analyzing the sensitivity, we recognized the greatest current threat and in response, determined the appropriate UUV countermeasures. The results showed that the dynamic Bayesian method has great practical significance and value for threat assessment.
收录类别:EI;SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061177506&doi=10.1109%2fACCESS.2019.2891940&partnerID=40&md5=98c1b59d69dc8cc77a84b836656ac133
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