• Title/Summary/Keyword: 국방연구원

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The Development of Rule-based AI Engagement Model for Air-to-Air Combat Simulation (공대공 전투 모의를 위한 규칙기반 AI 교전 모델 개발)

  • Minseok, Lee;Jihyun, Oh;Cheonyoung, Kim;Jungho, Bae;Yongduk, Kim;Cheolkyu, Jee
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.6
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    • pp.637-647
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    • 2022
  • Since the concept of Manned-UnManned Teaming(MUM-T) and Unmanned Aircraft System(UAS) can efficiently respond to rapidly changing battle space, many studies are being conducted as key components of the mosaic warfare environment. In this paper, we propose a rule-based AI engagement model based on Basic Fighter Maneuver(BFM) capable of Within-Visual-Range(WVR) air-to-air combat and a simulation environment in which human pilots can participate. In order to develop a rule-based AI engagement model that can pilot a fighter with a 6-DOF dynamics model, tactical manuals and human pilot experience were configured as knowledge specifications and modeled as a behavior tree structure. Based on this, we improved the shortcomings of existing air combat models. The proposed model not only showed a 100 % winning rate in engagement with human pilots, but also visualized decision-making processes such as tactical situations and maneuvering behaviors in real time. We expect that the results of this research will serve as a basis for development of various AI-based engagement models and simulators for human pilot training and embedded software test platform for fighter.

Development Direction of the Military Intelligent Platform Infrastructure (국방 지능형 플랫폼 기반체계 발전방향)

  • Pyeon, Dohoo;Kim, Sungtae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.58-61
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    • 2022
  • As data is evaluated as a key asset for digital transformation, efficient and stable management of data, smooth sharing data, and provision of services using data are also required in the defense. To support this, the Korean military is laying the foundation for the Military Artificial Intelligence Platform which is a defense data management infrastructure. In this paper, we examine the data strategies and data platform promotion directions of Korea and major advanced groups, and we look for suggestion and present the direction of development of the Military Intelligent Platform. We are expected that it can contribute to the establishment of a safe and efficient defense data management infrastructure for the Korean military.

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Camouflaged Adversarial Patch Attack on Object Detector (객체탐지 모델에 대한 위장형 적대적 패치 공격)

  • Jeonghun Kim;Hunmin Yang;Se-Yoon Oh
    • Journal of the Korea Institute of Military Science and Technology
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    • v.26 no.1
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    • pp.44-53
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    • 2023
  • Adversarial attacks have received great attentions for their capacity to distract state-of-the-art neural networks by modifying objects in physical domain. Patch-based attack especially have got much attention for its optimization effectiveness and feasible adaptation to any objects to attack neural network-based object detectors. However, despite their strong attack performance, generated patches are strongly perceptible for humans, violating the fundamental assumption of adversarial examples. In this paper, we propose a camouflaged adversarial patch optimization method using military camouflage assessment metrics for naturalistic patch attacks. We also investigate camouflaged attack loss functions, applications of various camouflaged patches on army tank images, and validate the proposed approach with extensive experiments attacking Yolov5 detection model. Our methods produce more natural and realistic looking camouflaged patches while achieving competitive performance.

A Study on Optimal Placement of Underwater Target Position Tracking System considering Marine Environment (해양환경을 고려한 수중기동표적 위치추적체계 최적배치에 관한 연구)

  • Taehyeong Kim;Seongyong Kim;Minsu Han;Kyungjun Song
    • Journal of the Korea Institute of Military Science and Technology
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    • v.26 no.5
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    • pp.400-408
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    • 2023
  • The tracking accuracy of buoy-based LBL(Long Base Line) systems can be significantly influenced by sea environmental conditions. Particularly, the position of buoys that may have drifted due to sea currents. Therefore it is necessary to predict and optimize the drifted-buoy positions in the deploying step. This research introduces a free-drift simulation model using ocean data from the European CMEMS. The simulation model's predictions are validated by comparing them to actual sea buoy drift tracks, showing a substantial match in averaged drift speed and direction. Using this drift model, we optimize the initial buoy layout and compare the tracking performance between the center hexagonal layout and close track layout. Our results verify that the optimized layout achieves lower tracking errors compared to the other two layout.

Real-virtual Point Cloud Augmentation Method for Test and Evaluation of Autonomous Weapon Systems (자율무기체계 시험평가를 위한 실제-가상 연계 포인트 클라우드 증강 기법)

  • Saedong Yeo;Gyuhwan Hwang;Hyunsung Tae
    • Journal of the Korea Institute of Military Science and Technology
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    • v.27 no.3
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    • pp.375-386
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    • 2024
  • Autonomous weapon systems act according to artificial intelligence-based judgement based on recognition through various sensors. Test and evaluation for various scenarios is required depending on the characteristics that artificial intelligence-based judgement is made. As a part of this approach, this paper proposed a LiDAR point cloud augmentation method for mixed-reality based test and evaluation. The augmentation process is achieved by mixing real and virtual LiDAR signals based on the virtual LiDAR synchronized with the pose of the autonomous weapon system. For realistic augmentation of test and evaluation purposes, appropriate intensity values were inserted when generating a point cloud of a virtual object and its validity was verified. In addition, when mixing the generated point cloud of the virtual object with the real point cloud, the proposed method enhances realism by considering the occlusion phenomenon caused by the insertion of the virtual object.

Adversarial Attacks for Deep Learning-Based Infrared Object Detection (딥러닝 기반 적외선 객체 검출을 위한 적대적 공격 기술 연구)

  • Kim, Hoseong;Hyun, Jaeguk;Yoo, Hyunjung;Kim, Chunho;Jeon, Hyunho
    • Journal of the Korea Institute of Military Science and Technology
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    • v.24 no.6
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    • pp.591-601
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    • 2021
  • Recently, infrared object detection(IOD) has been extensively studied due to the rapid growth of deep neural networks(DNN). Adversarial attacks using imperceptible perturbation can dramatically deteriorate the performance of DNN. However, most adversarial attack works are focused on visible image recognition(VIR), and there are few methods for IOD. We propose deep learning-based adversarial attacks for IOD by expanding several state-of-the-art adversarial attacks for VIR. We effectively validate our claim through comprehensive experiments on two challenging IOD datasets, including FLIR and MSOD.

우리나라 장군사회와 군사문제 "신한국군 리포트", "선진국방의 지평"

  • Ji, Man-Won
    • The Korean Publising Journal, Monthly
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    • s.235
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    • pp.30-30
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    • 1998
  • 기자들이 쓴 "신한국군 리포트"에는 한국군 장군들의 모습이 여과없이 적나라하게 묘사돼 있어 마치 현장을 보는 것과 같은 느낌이 들게 한다. 국방연구원에서 재직한 학자들의 저술인 "선진국방의 지평"에는 입문서 성격의 책으로 구체적인 대안제시가 아쉽다.

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