• Title/Summary/Keyword: Unmanned Combat Aircraft System

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Computation of Flowfield and Infrared Signature in Aircraft Exhaust System for IR Reduction Design (항공기 후방동체 열유동장 및 IR 신호 예측 시스템)

  • Moon, Hyuk;Yang, Young-Rok;Chun, Soo-Hwan;Choi, Seong-Man;Myong, Rho-Shin;Cho, Tae-Hwan
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.39 no.7
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    • pp.652-659
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    • 2011
  • A computational system to predict flowfield and infrared signature in aircraft exhaust system is developed. As the first step, a virtual mission profile is considered and an engine is selected through a performance analysis. Then a nozzle that meets the requirement of each mission is designed. The internal flow in the exhaustion nozzle at the maximum thrust is analyzed using a state-of-the-art CFD code. In addition, a system to combine information of the skin temperature distribution of the nozzle and after-body surface with an infrared prediction code is developed. Finally, qualitative results for the infrared signature reduction design are obtained by investigating the infrared signature level under various conditions.

A Study on Deep Learning based Aerial Vehicle Classification for Armament Selection (무장 선택을 위한 딥러닝 기반의 비행체 식별 기법 연구)

  • Eunyoung, Cha;Jeongchang, Kim
    • Journal of Broadcast Engineering
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    • v.27 no.6
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    • pp.936-939
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    • 2022
  • As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

A Study on the Database Design in the MDO Environment (다분야 통합환경에서의 데이터베이스 설계 연구)

  • Hwang, Jin Yong;Jeong, Ju Yeong;Lee, Jae U;Byeon, Yeong Hwan
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.31 no.5
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    • pp.25-36
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    • 2003
  • Aircraft design pursues integrated design efforts by considering all design elements together. In the integrated design environment, it is crucial for the design data to be consistent, free of errorm, and most recent. Database design process consists of the analysis of the data which shall be stored and managed, the construction of the E-R Diagram, and the mapping of the database table. As a DBMS (DataBase Management System), Oracle 8i is employed to design and construct the database. The database design methodology is devised to apply for the several MDO(Multidisciplinary Design Optimization) techniques like MDF(MultiDisplinary Feasible), IDF(Individual Discipline Feasible), and CO(Collaborative Optimization). The defined process is demonstrated through a couple of design examples, including a simple numerical example and a UCAV(Unmanned Combat Aerial Vehicle) design optimization.