• Title/Summary/Keyword: Drone Identification

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Trends in Low Altitude Small Drone Identification Technology and Standardization (저고도 소형드론 식별 기술 및 표준화 동향)

  • Kang, K.M.;Park, J.C.;Choi, S.N.;Oh, J.H.;Hwang, S.H.
    • Electronics and Telecommunications Trends
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    • v.34 no.6
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    • pp.164-174
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    • 2019
  • This article presents low altitude small drone identification trends at home and abroad. To reduce the dysfunction caused by the proliferation of drones worldwide, there is a growing interest in remote identification technologies that can identify the basic information of the drone. First, this article introduces policy trends in major countries. US, Europe, and China have recently provided recommendations regarding technologies available for the remote identification and tracking of a drone. Next, standardization activities on identification communications and identification systems are introduced. For this, standards organizations for the small drone identification, such as the International Organization for Standardization, IEEE 802, Radio Technical Commission for Aeronautics, International Civil Aviation Organization, and $3^{rd}$ Generation Partnership Project, are investigated. Finally, drone identification technology trends are introduced. In the US and Europe, various drone identification technologies have been studied to identify a drone owner and drone registration information with a drone identifier. In South Korea, drone identification technology is still in its infancy, whereas drone detection and physical counterattack technologies are somewhat more developed. As such, major drone manufacturers are also currently studying and developing drone identification systems.

A study on Improving the Performance of Anti - Drone Systems using AI (인공지능(AI)을 활용한 드론방어체계 성능향상 방안에 관한 연구)

  • Hae Chul Ma;Jong Chan Moon;Jae Yong Park;Su Han Lee;Hyuk Jin Kwon
    • Journal of the Korean Society of Systems Engineering
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    • v.19 no.2
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    • pp.126-134
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    • 2023
  • Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.

Anti-Drone Technology for Drone Threat Response: Current Status and Future Directions

  • Jinwoo Jeong;Isaac Sim;Sangbom Yun;Junghyun Seo
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.115-127
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    • 2023
  • In this paper, we have undertaken a comprehensive investigation into the current state of anti-drone technology due to the increasing concerns and risks associated with the widespread use of drones. We carefully analyze anti-drone technology, dividing it into three crucial domains: detection, identification, and neutralization methods. This categorization enables us to delve into intricate technical details, highlighting the diverse techniques used to counter evolving drone threats. Additionally, we explore the legal and regulatory aspects of implementing anti-drone technology. Our research also envisions potential directions for advancing and evolving anti-drone tech to ensure its effectiveness in an ever-changing threat environment.

Analysis of Domestic and International Patent Trends in Anti-drone Technology through Patent Application Status Survey (특허 출원 현황조사를 통한 안티드론 기술의 국내외 특허 동향 분석)

  • Jae-Hyo Hwang;Ki-Jung Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.6
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    • pp.1217-1228
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    • 2023
  • In this paper, technical and patent analysses of anti-drone technology, which aim to neutralize drone attacks are conducted. We conducted research on the technical definition of anti-drone, the technical elements of anti-drone systems, and investigated the patents related to anti-drone and drone filed domestically and internationally over the past 10 years, starting from 2011. For domestic patents, we examined the number of patent applications related to anti-drone and the overall domestic patent applications over the past 10 years. Regarding international filings, we investigated the patent applications related to anti-drone filed in the United States, Europe, Japan, China, and under the PCT system in the past 10 years. We conducted a search for patents related to anti-drone, including neutralization techniques identified under the keyword "anti-drone," patents related to drone detection and identification techniques, and patents related to drone neutralization techniques. Through the conducted research, a total of 91 patents were filed for drone detection techniques. Out of these, 5 patents, accounting for 5.5%, were filed by public institutions. In the case of patents filed for drone identification techniques, there were a total of 174 patents. Among these, 4 patents, which is 2.3%, were filed by public institutions.

A Survey on Identification Technology of Low-altitude Small Drones and Suggestion of an Identification System (저고도 소형드론 식별기술 동향 조사 및 식별시스템 제안)

  • Shin, Jaeho;Shin, Seungchan;Ko, Sangho;Kang, Kyu-min;Hwang, Sunghyun
    • Journal of Aerospace System Engineering
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    • v.14 no.5
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    • pp.18-25
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    • 2020
  • This paper provides the basic data of low-altitude small drone management technology to solve the problem of drone's dysfunction that generally increases with the demand of the drone. Accordingly, various low-altitude small drone identification technology employed in many countries were investigated and analyzed. Herein, the research cases which have been developed to obtain diverse information such as the flight's plan, pilot's identity and contact number, and the flight's information such as the location and speed of small drones were mainly investigated. Furthermore, the list of the features of each case was analyzed. Moreover, the present paper suggests a drone identification system configuration which complements the problems of existing technologies and verifies the proposed system through a flight test.

SVM-based Drone Sound Recognition using the Combination of HLA and WPT Techniques in Practical Noisy Environment

  • He, Yujing;Ahmad, Ishtiaq;Shi, Lin;Chang, KyungHi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.10
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    • pp.5078-5094
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    • 2019
  • In recent years, the development of drone technologies has promoted the widespread commercial application of drones. However, the ability of drone to carry explosives and other destructive materials may bring serious threats to public safety. In order to reduce these threats from illegal drones, acoustic feature extraction and classification technologies are introduced for drone sound identification. In this paper, we introduce the acoustic feature vector extraction method of harmonic line association (HLA), and subband power feature extraction based on wavelet packet transform (WPT). We propose a feature vector extraction method based on combined HLA and WPT to extract more sophisticated characteristics of sound. Moreover, to identify drone sounds, support vector machine (SVM) classification with the optimized parameter by genetic algorithm (GA) is employed based on the extracted feature vector. Four drones' sounds and other kinds of sounds existing in outdoor environment are used to evaluate the performance of the proposed method. The experimental results show that with the proposed method, identification probability can achieve up to 100 % in trials, and robustness against noise is also significantly improved.

Efficient Drone Detection method using a Radio-Frequency (RF를 이용한 효과적인 드론 탐지 기법)

  • Choi, Hong-Rak;Jeong, Won-Ho;Kim, Kyung-Seok
    • Journal of Satellite, Information and Communications
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    • v.12 no.4
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    • pp.26-33
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    • 2017
  • A drone performs a mission through remote control or automatic control, which uses wireless communications technology. Recently the increasing use of drones, the drone signal RF detection is necessary. In this paper, we propose an efficient dron RF detection method through simulations considering Wi-Fi, Bluetooth and dedicated protocol dron communication method in ISM(Industry Science Medical) band.. After configuring an environment where a common terminal and a drone signal are mixed, a general terminal and a drone signal are distinguished from each other by using a RF characteristic according to a dron movement. The proposed drone RF detection method is the WRMD(Windowed RSSI Moving Detection) operation and the Doppler frequency identification method. The simulation environments consist to mixed for two signals and four signals. We analysis the performance to proposed drone RF detection technique thorough detection rate.

An Analysis on Anti-Drone Technology Trends of Domestic Companies Using News Crawling on the Web (뉴스 기사의 크롤링을 통한 국내 기업의 안티 드론에 사용되는 기술 현황 분석)

  • Kim, Kyuseok
    • Journal of Advanced Navigation Technology
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    • v.24 no.6
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    • pp.458-464
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    • 2020
  • Drones are being spreaded for the purposes such as construction, logistics, scientific research, recording, toy and so on. However, anti-drone related technologies which make the opposite drones neutralized are also widely being researched and developed because some drones are being used for crime or terror. The range of anti-drone related technologies can be divided into detection, identification and neutralization. The drone neutralization methods are divided into Soft-kill one which blocks the detected drones using jamming and Hard-kill one which destroys the detected ones physically. In this paper, Google and Naver domestic news articles related to anti-drone were gathered. Analyzing the domestic news articles, 8 of related technologies using RF, GNSS, Radar and so on were found. Regarding as this, the general features and usage status of those technologies were described and those on anti-drone for each company and agency were gathered and analyzed.

A Proposal for Drone Entity Identification and Secure Information Provision Technology Using Quantum Entropy Chip-Based Cryptographic Module in WLAN Environment (무선랜 환경에서 양자 엔트로피 칩 기반 암호모듈을 적용한 드론 피아식별과 안전한 정보 제공 기술 제안)

  • Jung, Seowoo;Yun, Seunghwan;Yi, Okyeon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.5
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    • pp.891-898
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    • 2022
  • Along with global interest, drones are expanding the base of utilization such as transportation of goods, forest protection, and safety management, and cluster flights are being applied in various fields such as military operations and environmental monitoring. Currently, specialized networks such as e-UM 5G for services in specific industries are being established in Korea. In this regard, drone systems are also moving to establish specialized networks to provide services that are fused with AI and autonomous flight. As drones converge with various services, various security threats in various environments are also subordinated, and in response, requirements and guidelines for drone security are being prepared in Korea. In this paper, we propose a technology method for peer identification and safe information provision between cluster flight drones by utilizing a cryptographic module equipped with wireless LAN and quantum entropy-based random number generator in a cluster flight system and a mobile communication network such as e-UM 5G.

Identification of Aquatic Plants in the Muncheon Water Reservoir Using Drone-based Information (드론원격정보를 활용한 저수지 수생식물 분포 파악: 경북 문천저수지에서의 적용 예)

  • Lee, Geun-Sang;Kim, Sung-Wook;Lee, Khil-Ha
    • Journal of Environmental Science International
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    • v.26 no.5
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    • pp.685-689
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    • 2017
  • Aquatic plants serve the crucial function of helping to balance water reservoir ecosystem, as they filter and remove major minerals required for algal growth such as nitrogen, ammonia, and nitrates. Aquatic plants provide food, shade, and protection for the aquatic biome in and around the reservoir. Thus, it is important to accurately determine the existence and areal extent of the aquatic plants. In the present study drone-based facilities were used for this purpose. In the Muncheon water reservoir, Gyeongbuk, the Normalized Difference Vegetation Index (NDVI) and Surface Algal Bloom Index (SABI) were used to determine the existence status of the aquatic plants. The data so obtained exhibited reasonable accuracy; drone-based facilities can be used in future to identify the areal extent of aquatic plants.