• Title/Summary/Keyword: air defense network

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A study on unmanned watch system using ubiquitous sensor network technology (유비쿼터스 센서 네트워크 기술을 활용한 무인감시체계 연구)

  • Wee, Kyoum-Bok
    • Journal of National Security and Military Science
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    • s.7
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    • pp.271-303
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    • 2009
  • "Ubiquitous sensor network" definition is this-Someone attaches electro-magnetic tag everything which needs communication between man to man, man to material and material to material(Ubiquitous). By using attached every electro-magnetic tag, someone detects it's native information as well as environmental information such as temperature, humidity, pollution and infiltration information(Sensor). someone connects it realtime network and manage generated information(Network). 21st century's war is joint combined operation connecting with ground, sea and air smoothly in digitalized war field, and is systematic war provided realtime information from sensor to shooter. So, it needs dramatic development on watch reconnaissance, command and control, pinpoint strike etc. Ubiquitous computing and network technologies are essential in national defense to operate 21st century style war. It is possible to use many parts such as USN combined smart dust and sensor network to protect friend unit as well as to watch enemy's deep area by unmanned reconnaissance, wearable computer upgrading soldier's operational ability and combat power dramatically, RFID which can be used material management as well as on time support. Especially, unmanned watch system using USN is core part to transit network centric military service and to get national defense efficiency which overcome the dilemma of national defense person resource reducing, and upgrade guard quality level, and improve combat power by normalizing guardian's bio rhythm. According to the test result of sensor network unmanned watch system, it needs more effort and time to stabilize because of low USN technology maturity and using maturity. In the future, USN unmanned watch system project must be decided the application scope such as application area and starting point by evaluating technology maturity and using maturity. And when you decide application scope, you must consider not only short period goal as cost reduction, soldier decrease and guard power upgrade but also long period goal as advanced defense ability strength. You must build basic infra in advance such as light cable network, frequency allocation and power facility etc. First of all, it must get budget guarantee and driving force for USN unmanned watch system project related to defense policy. You must forwarded the USN project assuming posses of operation skill as procedure, system, standard, training in advance. Operational skill posses is come from step by step application strategy such as test phase, introduction phase, spread phase, stabilization phase and also repeated test application taking example project.

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Prospective Scheme of Network Based Battle Management System in AMD (공중.미사일방어의 네트워크중심 전장관리체계 발전방안)

  • Kwon, Yong-Soo;Ham, Byung-Woon;Kim, Ha-Chul
    • Journal of the Korea Institute of Military Science and Technology
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    • v.9 no.4
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    • pp.50-60
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    • 2006
  • This work describes a basic concept of network based battle management system in AMD(Air & Missile Defense). The AMD operation inherently is joint concept that each single service do not satisfy the requirements of AMD theater operation. It is integrated system of joint forces that is operated simultaneously. The analysis of the future battlespace and air & missile threat is shown. From this analysis the prospective scheme of network based battle management system in building Korean future AMD is presented.

Evaluation of the Use of Inertial Navigation Systems to Improve the Accuracy of Object Navigation

  • Iasechko, Maksym;Shelukhin, Oleksandr;Maranov, Alexandr;Lukianenko, Serhii;Basarab, Oleksandr;Hutchenko, Oleh
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.71-75
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    • 2021
  • The article discusses the dead reckoning of the traveled path based on the analysis of the video data stream coming from the optoelectronic surveillance devices; the use of relief data makes it possible to partially compensate for the shortcomings of the first method. Using the overlap of the photo-video data stream, the terrain is restored. Comparison with a digital terrain model allows the location of the aircraft to be determined; the use of digital images of the terrain also allows you to determine the coordinates of the location and orientation by comparing the current view information. This method provides high accuracy in determining the absolute coordinates even in the absence of relief. It also allows you to find the absolute position of the camera, even when its approximate coordinates are not known at all.

Numerical Prediction of Aviation Fuel Temperatures in Unmanned Air Vehicles

  • Baek, Nak-Gon;Lim, Jin-Shik
    • International Journal of Aeronautical and Space Sciences
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    • v.12 no.4
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    • pp.379-384
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    • 2011
  • This paper performs numerical prediction of fuel temperature in the fuel tanks of unmanned air vehicles for both ground static non-operating and in flight transient conditions. The calculation is carried out using a modified Dufort-Frankel scheme. For this calculation, it is assumed that a non-operating vehicle on the ground is subjected to repeating daily cycles of ambient temperature with solar radiation and wind under 1%, with a 20% probability of hot day conditions. The energy conservation equation is used as the governing equation to calculate heat transfer between the fuel tank surface and the ambient environment. Results of the present analysis may be used as the estimated initial values of fuel temperatures in a vehicle's fuel tank for the purpose of analyzing transient fuel temperatures during various flight missions. This research also demonstrates that the fuel temperature of the front tank is higher than that of the rear tank, and that the difference between the two temperatures increases in the later phases of flight due to the consumption of fuel.

Selection of Important Variables in the Classification Model for Successful Flight Training (조종사 비행훈련 성패예측모형 구축을 위한 중요변수 선정)

  • Lee, Sang-Heon;Lee, Sun-Doo
    • IE interfaces
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    • v.20 no.1
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    • pp.41-48
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    • 2007
  • The main purpose of this paper is cost reduction in absurd pilot positive expense and human accident prevention which is caused by in the pilot selection process. We use classification models such as logistic regression, decision tree, and neural network based on aptitude test results of 505 ROK Air Force applicants in 2001~2004. First, we determine the reliability and propriety against the aptitude test system which has been improved. Based on this conference flight simulator test item was compared to the new aptitude test item in order to make additional yes or no decision from different models in terms of classification accuracy, ROC and Response Threshold side. Decision tree was selected as the most efficient for each sequential flight training result and the last flight training results predict excellent. Therefore, we propose that the standard of pilot selection be adopted by the decision tree and it presents in the aptitude test item which is new a conference flight simulator test.

NBC Hazard Prediction Model using Sensor Network Data (센서네트워크 데이터를 활용한 화생방 위험예측 모델)

  • Hong, Se-Hun;Kwon, Tae-Wook
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.5
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    • pp.917-923
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    • 2010
  • The local area weather information is very important element to estimate where the air-pollutant will flow. But the existing NBC hazard prediction model does not consider the local area weather information. So, in this paper, we present SN-HPM that uses the local area wether information to perform more accurate and reliable estimate, and embody it to program.

Multi-objective Optimization Model for C-UAS Sensor Placement in Air Base (공군기지의 C-UAS 센서 배치를 위한 다목적 최적화 모델)

  • Shin, Minchul;Choi, Seonjoo;Park, Jongho;Oh, Sangyoon;Jeong, Chanki
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.2
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    • pp.125-134
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    • 2022
  • Recently, there are an increased the number of reports on the misuse or malicious use of an UAS. Thus, many researchers are studying on defense schemes for UAS by developing or improving C-UAS sensor technology. However, the wrong placement of sensors may lead to a defense failure since the proper placement of sensors is critical for UAS defense. In this study, a multi-object optimization model for C-UAS sensor placement in an air base is proposed. To address the issue, we define two objective functions: the intersection ratio of interested area and the minimum detection range and try to find the optimized placement of sensors that maximizes the two functions. C-UAS placement model is designed using a NSGA-II algorithm, and through experiments and analyses the possibility of its optimization is verified.

A Study of Image Classification using HMC Method Applying CNN Ensemble in the Infrared Image

  • Lee, Ju-Young;Lim, Jae-Wan;Koh, Eun-Jin
    • Journal of Electrical Engineering and Technology
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    • v.13 no.3
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    • pp.1377-1382
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    • 2018
  • In the marine environment, many clutters have similar features with the marine targets due to the diverse changes of the air temperature, water temperature, various weather and seasons. Also, the clutters in the ground environment have similar features due to the same reason. In this paper, we proposed a robust Hybrid Machine Character (HMC) method to classify the targets from the clutters in the infrared images for the various environments. The proposed HMC method adopts human's multiple personality utilization and the CNN ensemble method to classify the targets in the ground and marine environments. This method uses an advantage of the each environmental training model. Experimental results demonstrate that the proposed method has better success rate to classify the targets and clutters than previously proposed CNN classification method.

Development and Analysis of Real-time Distributed Air Defense System Simulator Using a Software Framework (소프트웨어 프레임워크를 이용한 대공유도무기 실시간 분산 시뮬레이터 개발 및 분석)

  • Cho, Byung-Gyu;Youn, Cheong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.8 no.4 s.23
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    • pp.58-67
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    • 2005
  • To overcome limitations of test scope, schedule and cost, M&S(Modeling & Simulation) technique has been applied for T&E(Test and Evaluation) of the state-of-art weapon systems. This paper proposes an air defense simulation software framework to reduce both redundancy an[1 programming errors in system simulator. The proposed framework consists of a 'model' and a 'middleware' The 'middleware' is a reliable communication service layer that supports not only HLA(High Level Architecture) which is an international standard in M&S but also TCP/IP, UDP and etc. The main role of 'model' is to schedule and to run the real-time distributed simulation. The proposed framework has been applied to M-SAM(Middle range Surface to Air Missile) system simulator. The proposed framework's scheduling and communication performance results are satisfactory and were measured by hardwired NTP(Network Timer Protocol) time-stamp with GPS(Global Positioning System) timer for better precision.

A Study of CR-DuNN based on the LSTM and Du-CNN to Predict Infrared Target Feature and Classify Targets from the Clutters (LSTM 신경망과 Du-CNN을 융합한 적외선 방사특성 예측 및 표적과 클러터 구분을 위한 CR-DuNN 알고리듬 연구)

  • Lee, Ju-Young
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.68 no.1
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    • pp.153-158
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    • 2019
  • In this paper, we analyze the infrared feature for the small coast targets according to the surrounding environment for autonomous flight device equipped with an infrared imaging sensor and we propose Cross Duality of Neural Network (CR-DuNN) method which can classify the target and clutter in coastal environment. In coastal environment, there are various property according to diverse change of air temperature, sea temperature, deferent seasons. And small coast target have various infrared feature according to diverse change of environment. In this various environment, it is very important thing that we analyze and classify targets from the clutters to improve target detection accuracy. Thus, we propose infrared feature learning algorithm through LSTM neural network and also propose CR-DuNN algorithm that integrate LSTM prediction network with Du-CNN classification network to classify targets from the clutters.