• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1425-1431
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• 2005

In this paper, we consider the ISR(Intelligence, Surveillance, and Reconnaissance) system which collects the imagery intelligence from an airplane and CDL(common data link) communication system which transports the information obtained by the ISR system. The IMINT(imagery intelligence) consists of MPEG-2 transport stream packets and they transmit through CDL. We have some simulations for communication performances of CDL and show performance improvements using convolutional coding. We have compared BER performances under AWGN channel and fading channel which is caused by the velocity of an airplane.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.48-51
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• 2008

지능화된 국방 정보 시스템의 구축을 위해서는 정보를 수집하고, 수집된 정보를 분석하며, 이를 바탕으로 상황을 인지할 수 있는 시스템이 필요하다. 이러한 시스템의 개발을 위해서는, 단편적인 정보를 저장, 조회할 수 있는 데이터 베이스 구조보다는, 수집된 정보들간의 유기적인 관계를 설명할 수 있는 온톨로지 구조가 적합하다. 이를 위해 본 논문에서는 지능화된 국방 정보시스템 중 사람, 신호, 이미지로부터 획득한 정보를 통합·분석하기 위한 에이전트에서 사용될 온톨로지의 설계에 관하여 다룰 것이다. 본 온톨로지는 상위 온톨로지로는 SUMO를 사용하여 각 도메인 온톨로지로부터 들어온 정보를 통합할 수 있도록 하였고, 도메인 온톨로지로는 HUMINT, SIGINT, IMINT 를 사용하여 각 종류의 신호로부터 들어오는 정보를 분석할 수 있도록 하였다. 또한 각각의 온톨로지간의 유기적 관계를 구성하였다.

• 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..

• Convergence Security Journal
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• v.3 no.2
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• pp.41-55
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• 2003

Today the traditional national intelligence activities which are mainly based on classified informations are confronted with several problems. These are excessive collection cost, morality of intelligence activity, objectivity of intelligence, intelligence dead zone and timeliness of intelligence etc. On the other hand, circumstances of national intelligence activity are rapidly changed. Those are rapid growth of internet, transformation of classified information into open one and rapid growth of intelligence capabilities of private sector. To cope these problems and circumstances, we reevaluated OSINT(Open Source INTelligence) which is collected from all kinds of open source informations on the internet. First, we classified OSINT into four categories corresponding to the traditional classified collection methods i.e., IMINT, SIGINT, HUMINT and MASINT. And we evaluate the value of OSINT in comparison with classified collection methods. Finally a system for national intelligence activity based on all kinds of open source intelligence on the internet is proposed, described and compared with the system of traditional national intelligence activity.