• Journal of Satellite, Information and Communications
• /
• v.12 no.4
• /
• pp.26-33
• /
• 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.

• Journal of Satellite, Information and Communications
• /
• v.12 no.2
• /
• pp.99-103
• /
• 2017

Recently, acccording to price decline and miniaturization of drone, it is increased dramatically that drone usage in various category including military and private sectors. In accordance with popular usage, There is a increasing risk of safety accident, national security and public privacy problem. Hence there is a high demand for study and analysis applicable to the related technology and anti-drone method including drone detection and jamming. In general, it is extremely difficult to detect and recognize drones using conventional sensors. In this paper, we classify drone detection technology and Drone detection experiments are performed using CW RADAR to obtain and analyze micro-doppler pattern. This preliminary study aims to provide fundamental theory on radar drone detection and experimental test results such that in-depth anti-drone technology can be established in future.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.5
• /
• pp.881-890
• /
• 2022

As individual and group users actively use drones, the risks (Intrusion, Information leakage, and Sircraft crashes and so on) in no-fly zones are also increasing. Therefore, it is necessary to build a system that can detect drones intruding into the no-fly zone. General acoustic drone detection researches do not derive location-independent performance by directly learning drone sound including environmental noise in a deep learning model to overcome environmental noise. In this paper, we propose a drone detection system that collects sounds including environmental noise, and detects drones by removing noise from target sound. After removing environmental noise from the collected sound, the proposed system predicts the drone sound using Mel spectrogram and CNN deep learning. As a result, It is confirmed that the drone detection performance, which was weak due to unstudied environmental noises, can be improved by more than 7%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.63-66
• /
• 2019

Recently, as the technology of drones develops, a malicious attack using a drones becomes a problem, and an anti-drone technology for detecting an attack dron for a malicious attack is required. However, currently used drone detection systems are expensive and require a lot of manpower. Therefore, in this paper, we propose an anti - drone method using the analysis and algorithms of the anti - drone that can monitor the attack drones. In this paper, we identify and detect attack drones using sniffing, and propose capture and deception algorithm through spoofing using current GPS based detection system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• fall
• /
• pp.335-337
• /
• 2021

최근 드론의 용도는 취미, 공연, 농업, 안전, 군사, 연구, 물자수송 등 다양한 분야와 목적으로 활용되고 있다. 더불어 드론의 불법적 활용으로 인한 안전 및 법적 문제 또한 빈번히 발생하고 있어, 이런 문제들을 예방하기 위한 드론의 탐지 기술이 활발히 연구되고 있다. 본 논문은 카메라로 촬영된 영상에서 조류와 같은 다른 객체와 구별하여 드론을 탐지하는 기술과 상공에서 바라본 객체들을 탐지하는 기술을 구현한다. 제안 방법은 딥러닝 기반의 YOLOv4를 사용하였다. UAV_123 데이터세트로 학습한 실험 결과, mAP는 85%, Recall은 85%, Precision은 81%의 정확도를 보였다. 제안 방법은 인명 구조, 배송, 건축 뿐만 아니라 안티 드론 시장에서도 효과적으로 활용될 수 있을 것으로 기대된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.3
• /
• pp.83-92
• /
• 2018

This paper uses the Apollonius Circle technique to estimate the position of a target that generates a specific signal by using a drone, which is rapidly becoming a rapidly expanding industry. The existing direction finding method is performed through the vehicle on the ground or installed the antenna at a high position to detect the position of the target. However, the conventional direction finding method is difficult to configure the reception environment of the LOS signal, It is difficult. However, the direction finding using the drone is easy to construct and measure the LOS signal receiving environment using the drone flying at high altitude. In this study, we use the 3D 800MHz Path-Loss Model to reconstruct the signal by using the measurement data of the ground direction finding, reconstruct the signal by using the 3-D 800MHz Path-Loss Model, and use the Apollonius Circle method to estimate the position of the target. A simulation was performed to estimate the position of the target. Simulation was performed to determine the target position estimation performance by configuring the ground direction finding and the dron direction finding.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.3
• /
• pp.31-36
• /
• 2022

Recently, drones are being used in various fields, and drone technology is also developing. The risks of drones are increasing, then technology to detect drones is important. However, it is extremely difficult to detect and recognize drones due to the low level radar cross section of the commercial drones. In this paper, a signal processor structure that was mounted the miniaturized and light-weighted was designed. in order to process large amounts of data in real time, parallel processing was performed for each channel and an algorithm was applied to shorten the operation time in each step. As a test of verifing the detection performance through test, it was confirmed that the structure design works in real time.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.46 no.12
• /
• pp.975-985
• /
• 2018

The drones have been developed for military purposes and are now used in many fields such as logistics, communications, agriculture, disaster, defense and media. As the range of use of drones increases, cases of abuse of drones are increasing. It is necessary to develop anti-drone technology to detect the position of unwanted drones using the physical phenomena that occur when the drones fly. In this paper, we estimate the DOA(direction of arrival) of the drone by using the acoustic signal generated when the drone is flying. In addition, the dynamics model of the drones was applied to the unscented kalman filter to improve the microphone array detection performance and reduce the error of the position estimation. Through simulation, the drone detection performance was predicted and verified through experiments.

• Journal of the Korea Society for Simulation
• /
• v.28 no.1
• /
• pp.23-39
• /
• 2019

The use of drone-bots is demanded in times regarding the reduction of military force, the spread of the life-oriented thought, and the use of innovative technology in the defense through the fourth industrial revolution. Especially, the drone's surveillance and reconnaissance are expected to play a big role in the future battlefield. However, there are not many cases in which the concept of operation is studied scientifically. In this study, We propose search algorithms for reconnaissance drone through simulation analysis. In the simulation, the drone and target move linearly in continuous space, and the target is moving adopting the Random-walk concept to reflect the uncertainty of the battlefield. The research investigates the effectiveness of existing search methods such as Parallel and Spiral Search. We analyze the probabilistic analysis for detector radius and the speed on the detection probability. In particular, the new detection algorithms those can be used when an enemy moves toward a specific goal, PS (Probability Search) and HS (Hamiltonian Search), are introduced. The results of this study will have applicability on planning the path for the reconnaissance operations using drone-bots.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.01a
• /
• pp.225-226
• /
• 2021

드론산업과 센서의 발전에 따라 드론이 수행할 수 있는 능력이 넓어지고 있다. 본 논문에서는 드론에 장착되는 장비 중 카메라에 객체 탐지 기능을 넣어 퇴치할 대상을 인지하고 인식할 수 있음을 검증하고자한다. 이는 여러 산업에 새로운 패러다임을 제안하게 될 수 있는 방법이 될 것 이라 기대된다.