Intercept point prediction and mid-course guidance for anti-ballistic missile systems = 대 탄도탄 시스템의 중기유도를 위한 요격점 예측에 관한 연구

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dc.contributor.advisorTahk, Min-Jea-
dc.contributor.advisor탁민제-
dc.contributor.authorLee, Jun-Yong-
dc.date.accessioned2019-09-04T02:51:56Z-
dc.date.available2019-09-04T02:51:56Z-
dc.date.issued2016-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=849934&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/267320-
dc.description학위논문(석사) - 한국과학기술원 : 항공우주공학과, 2016.2,[vi, 53 p. :]-
dc.description.abstractIn this thesis, intercept point prediction of anti-ballistic missile system for low and middle altitude defense is researched. Intercept point or impact point means the point where the anti-ballistic missile and target ballistic missile meets at same time. First of all, equation of motion of re-entry ballistic missile is formulated. To predict a future position of the ballistic missile, prediction using neural network is implemented than numerical integration. Position and time information of the missile is tabulated by various simulation. Comparing with table of ballistic missile and predicted position of the ballistic missile determines intercept point and launch time of the missile. Determined predicted intercept point is used as destination of midcourse guidance. After seeker detects the target, terminal guidance intercepts the target precisely. Finally, impact angle and flight time of the missile is investigated by optimization method. Relationship between impact angle and flight time provides accurate information of the missile and more effective interception. This paper is focused on the method to predict the target ballistic missile. Without aerodynamic effects, ballistic missile draws Kepler orbit and Kepler’s equation solves the problem easily. With aerodynamic effects, well-trained neural network system predicts the position of ballistic missile. Finally, determination of predicted interception point and interception is simulated.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectAnti-ballistic missile▼aneural network theory▼apredicted intercept point▼atrajectory optimization-
dc.subject대탄도탄▼a신경망 이론▼a궤적 최적화▼a요격점 예측-
dc.titleIntercept point prediction and mid-course guidance for anti-ballistic missile systems = 대 탄도탄 시스템의 중기유도를 위한 요격점 예측에 관한 연구-
dc.typeThesis(Master)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :항공우주공학과,-
dc.contributor.alternativeauthor이준용-
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AE-Theses_Master(석사논문)
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