• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.7
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• pp.581-588
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• 2021

This paper deals with a beam scheduling method in fighter interleaving mode. Not only the priority of tasks but also operational requirements that air-to-ground and air-to-air search tasks should be executed alternatively are established to maximize high-quality of situational awareness. We propose a real-time heuristic beam scheduling method that is advanced from WMDD to satisfies the requirements. The proposed scheduling method is implemented in a simulation environment resembling the task processing mechanism and measurement model of a radar. Performance improvement in terms of task delay time is observed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1186-1195
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• 2013

In modern warfare, the main factor of triumph is superior situation awareness which leads rapid command decision and precisely guided munition, and TDL(Tactical Data Link) is the main communicational enabler. ROK forces currently operate Link-16 with allied forces and are also developing Korean national data link, Link-K which is also planned to be cooperated with Link-16. Assigning participant and track numbers needs agreement between ROK and allied forces, but ROK forces have exclusive authority in assigning numbers in Link-K. This paper proposes the effective method of exchange participant and track numbers between Link-16 and Link-K, and applicability verification in operational test and evaluation will be also presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.829-832
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• 2009

Recently, IT-centered convergence between different industries has undergone rapid expansion, accompanied by major advances in u-IT development and digital convergence. Notably, in the automotive-IT convergence sector, automotive sensors and electronic devices interact closely and intelligently with each other, thereby increasing driver safety and convenience and creating the optimal driving environment. This has led to the generation of value-added for the future-oriented automotive industry. Sensing technologies - which are used to monitor traffic situations and transmit correct information (or warnings) on the road traffic situation to car drivers, and to provide accurate information to road traffic controllers - represent both the birth of high-safety, intelligent automotive technologies and the key to automotive manufacturing. In view of these developments, this paper examines the characteristics and structure of the automotive sensor industry, and outlines the policy implications for the automotive sensor industry with regard to the development of the automotive-IT convergence industry.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.153-159
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• 2012

Driver's view has blind spot of automobile surroundings due to physical components of automobile architecture. Obstacles on blind spot are the cause of car destruction and car accidents. Cars which produced in recent have obstacle detection sensors and rear view cameras which provide information of obstacles on the blind sopt, and have also AVM(Around View Monitoring) which provides automobile surroundings for driver's safe driving. During a low-speed travel while parking or moving in a narrow street, a driver get help for safe driving by taking information of automobile surroundings using the above-mentioned devices. In this paper, we present a design and implementation of a 4-sided monitoring (4SM) system, which helps a driver see an integrated view of a vehicle's perimeter at a glance, using a car PC connected to four cameras installed on the front, rear, left, and right sides.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.738-746
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• 2016

As the trend of future war has been changed to network centric warfare, tactical data link should be needed for fast and accurate situation awareness. Nowadays, Korean air force conducts military operations by using aircrafts equipped with Link-16. The Link-16 can conduct multiple mission at the same time because it supports multi-net capability. Due to lack of frequency resource, the way to share the frequency with other systems has been studied and using L band with radar is considered as one of the candidates bands. However, the data link can be affected by the interference from radars when it shares the L-band because the L-band in Korea is already assigned to long-range detection radars. In this paper, we evaluate operational possibilities of tactical data link in the L-band based on Link-16.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.25.5-26
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• 2009

인류의 활동 무대가 우주공간으로 확대됨으로써 우주기상에 의한 피해를 최소화 할 수 있는 조치가 요구됨에 따라 우주기상에 대한 감시 및 예 경보 업무가 필요해 졌다. 미국은 이미 우주기상 감시와 예보의 필요성을 인식하고 해양대기청(NOAA), 미 공군(USAF), 항공우주국(NASA), 내무부(DOI), 에너지부(DOE), 과학재단(NSF)이 연합하여 1996년 국가우주기상 프로그램(National Space Weather Program)을 수립.추진하고 있다. 특히 정부연구 기관인 NOAA 산하 우주기상예보센터(Space Weather Prediction Center; SWPC)와 미 공군 기상국(AFWA)은 우주기상 자료 생산, 수집, 자료 센터 운용, 연구 지원 및 예 경보 업무를 공동으로 수행하고 있으며 관련 자료 및 정보의 교환 등 매우 밀접하게 상호협력하고 있다. 최근 정부는 과학기술 7대 중점투자 분야별 중점육성후보기술로서 우주감시체계개발기술을 포함한 국가과학기술기본계획(577전략)을 수립 발표하였으며, 대한민국 공군은 향후 우주군 창설을 목표로 우주전력 기반체계구축을 계획하고 있다. 국방부는 2012년 전시작전통제권 환수에 대비한 독자적인 작전지휘능력 확보가 필요한 상황이며, 미래의 한국군 독자적 네트웍 중심 전장(NCW: Network Central Warfare) 체계 구축을 위해서는 미 공군의 "우주기상작전센터"와 같은 우주기상 예 경보 체계 구축이 요구된다. 이 연구에서는 군의 독자적 우주작전능력 확보를 위한 우주기상 예 경보 체계 구축 방향을 제시하고자 사전기반 연구를 수행하였다. 그 내용으로 우주기상에 대한 개요 및 우주기상의 변화에 따른 국내외 영향을 조사하고 국내외 우주기상 예 경보 시스템을 소개하고자 한다. 또한, 미공군의 우주기상 활용 상태를 점검하여 한국 공군을 위한 우주기상 예 경보 체계 구축 및 인력과 기술 확보에 대한 방안을 제시하고자 한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4B
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• pp.269-277
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• 2012

The future battlefield environment has changed platform centric warfare into a network centric warfare. The NCO is a operational concept to improve combat power through information sharing, shared situational awareness, decision making and synchronized action based on powerful network grid. In addition, these operational environment is composed of physical, information, cognitive and social domains. The platform environment system is associated with the OSI 7 layer. However, OSI 7 layer is limited to express NCW environment including cognitive and social domains. Therefore, we requires a new model for expressing cognitive and social domains. After we developed a new model, this model applied to the NCW architecture taxonomy.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.91-101
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• 2010

Battle Management Language (BML) is defined as an unambiguous language intended to provide for command and control of simulated and live forces in U.S. It has been developed to connect between command and control system and Modeling & Simulation in the U.S., including NATO M&S Working Group. Its goal is to provide situational awareness and offer a path forward for interoperation of C2 systems and simulations. This study deals with BML development in U.S. that begins from army and is being expanded in multinational environment. It also proposes the BML application for C4I and M&S interoperation in the Korean forces. Recent developments of BML in U.S. have shown the potential for interoperation between C2 systems and simulations in a coalition environment. Finally, this study proposes a general BML application method and shows the example of its application to the Korea Joint Command Control System (KJCCS). It provides an architecture and a milestone for BML application in the Korean forces.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Journal of the Korea Society for Simulation
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• v.30 no.3
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• pp.1-9
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• 2021

Commander and staffs on the battlefield are aware of the situation and, based on the results, they perform military activities through their military decisions. Recently, with the development of information technology, the demand for artificial intelligence to support military decisions has increased. It is essential to identify, collect, and pre-process the data set for reinforcement learning to utilize artificial intelligence. However, data on enemies lacking in terms of accuracy, timeliness, and abundance is not suitable for use as AI learning data, so a training model is needed to collect AI learning data. In this paper, a methodology for learning artificial intelligence was presented using the constructive wargame model exercise data. First, the role and scope of artificial intelligence to support the commander and staff in the military decision-making process were specified, and to train artificial intelligence according to the role, learning data was identified in the Chang-Jo 21 model exercise data and the learning results were simulated. The simulation data set was created as imaginary sample data, and the doctrine of ROK Army, which is restricted to disclosure, was utilized with US Army's doctrine that can be collected on the Internet.