DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Choi, Han-Lim | - |
dc.contributor.advisor | 최한림 | - |
dc.contributor.author | Kim, Juhyung | - |
dc.date.accessioned | 2021-05-12T19:38:56Z | - |
dc.date.available | 2021-05-12T19:38:56Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=908470&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/284085 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 항공우주공학과, 2020.2,[v, 78 p. :] | - |
dc.description.abstract | In this dissertation, we have covered the results of some useful techniques for constructing a weapon control system for future ballistic missile defense systems. The future ballistic missile defense systems will focus on how effectively the defender can track and intercept a large number of simultaneous missile attacks. In order to accomplish this, first, the sensor resource assignment problem through automatic target handover is solved by Mixed Integer Linear Programming (MILP) and compared with the First-In-First-Out greedy algorithm as of heuristic technique to achieve seamless target tracking in networked radar systems. Secondly, for the effective trajectory and impact point prediction, which are the prerequisite of the previous task, we applied the well-known machine learning techniques that were not considered in the past as of model-free approach. The Recurrent Neural Network (RNN) and the Long-Short Term Memory (LSTM) method, which is suitable for time series data processing, were considered for trajectory and impact point estimation. The applicability of the technique is verified by using a simulation of the ballistic missile trajectory generator. In the appendix, a concept of distributed command system is established and its applicability was verified by the heuristic weapon-target assignment algorithm for the low layer air defense systems to be constructed. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Ballistic Missile Defense▼aCommand and Control Systems▼aBallistic target trajectory tracking and estimation▼aSensor Assignment▼aMixed Integer Linear Programming▼aWeapon-Target Assignment▼aDeep learning▼aLong-Short Term Memory Networks | - |
dc.subject | 탄도미사일 방어▼a교전통제 시스템▼a탄도탄 궤적 추적 및 예측▼a센서할당▼a분산 지휘체계▼a무기자원할당▼a혼합정수계획법▼a휴리스틱 알고리즘▼a딥러닝▼a순환신경망 | - |
dc.title | Information processing and resource allocation in intelligent radar systems against ballistic objects | - |
dc.title.alternative | 지능형 레이더 시스템의 탄도 표적에 대한 정보 처리 및 자원 할당에 관한 연구 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :항공우주공학과, | - |
dc.contributor.alternativeauthor | 김주형 | - |
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