• Journal of the Korea Convergence Society
• /
• v.8 no.4
• /
• pp.183-188
• /
• 2017

As the price of small UAVs is getting cheaper and its controllability is getting greatly increased, many aerial applications using both fixed-wing and hoverable UAVs have appeared in recent years. In this paper, a new aerial advertising method is proposed using four hoverable UAVs. Using the UAV swarm control method, four UAVs are maneuvered to carry a $7.07{\times}7.07m^2$ square banner along collision-free and predefined waypoints for aerial advertising. According to simulation results, it takes about 270 s for UAVs to perform aerial advertising in $669{\times}669m^2$ size area and the minimum distance among UAVs turns out to be 0.45 m which proves there is no any collision. Due to abrupt direction changes of UAVs along the predefined waypoints, UAVs cannot always maintain exact square formation and it results the maximum and minimum side lengths of square formation to be 10.35 m and 1.96 m, respectively. Also, the maximum and minimum diagonal lengths of square formation turn out to be 14.75 m and 2.78 m, respectively.

• Journal of the Korean Society of Visualization
• /
• v.17 no.3
• /
• pp.32-38
• /
• 2019

The dynamic stability of swarms is crucial in preventing collisions in clustered flights and safely moving along a defined path. Although there have been many simulation studies on dynamic stability, there have not been many experimental studies using real clusters due to the difficulty in implementation. In this study, we constructed a particle-lattice structure simulating bird flocks or drone swarms, and conducted experiments within turbulent flow. We identified a criterion that describes dynamically stable particle-lattice structures. The stability increased as this newly defined spatial index increased.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.2
• /
• pp.595-609
• /
• 2020

In this study, we propose a decentralized mathematical model for predictive control of a system of multi-autonomous unmanned aerial vehicles (UAVs), also known as drones. Being decentralized and autonomous implies that all members make their own decisions and fly depending on the dynamic information received from other unmanned aircraft in the area. We consider a variety of realistic characteristics, including time delay and communication locality. For this flocking flight, we do not possess control for central data processing or control over each UAV, as each UAV runs its collision avoidance algorithm by itself. The main contribution of this work is a mathematical model for stable group flight even in adverse weather conditions (e.g., heavy wind, rain, etc.) by adding Gaussian noise. Two of our proposed variance control algorithms are presented in this work. One is based on a simple biological imitation from statistical physical modeling, which mimics animal group behavior; the other is an algorithm for cooperatively tracking an object, which aligns the velocities of neighboring agents corresponding to each other. We demonstrate the stability of the control algorithm and its applicability in autonomous multi-drone systems using numerical simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.3
• /
• pp.779-800
• /
• 2024

Unmanned Aerial Vehicle (UAV) networks, also known as drone networks, have gained significant attention for their potential in various applications, including communication. UAV networks for communication involve using a fleet of drones to establish wireless connectivity and provide communication services in areas where traditional infrastructure is lacking or disrupted. UAV communication networks need to be highly secured to ensure the technology's security and the users' safety. The proposed survey provides a comprehensive overview of the current state-of-the-art UAV network security solutions. In this paper, we analyze the existing literature on UAV security and identify the various types of attacks and the underlying vulnerabilities they exploit. Detailed mitigation techniques and countermeasures for the protection of UAVs are described in this paper. The survey focuses on the implementation of novel technologies like Q-learning, blockchain, IRS, and mmWave. This paper discusses network simulation tools that range in complexity, features, and programming capabilities. Finally, future research directions and challenges are highlighted.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.3
• /
• pp.456-463
• /
• 2021

In this paper, Ultra Wide-Band(UWB) radar sensor is employed to detect flying drones and avoid collision in dense clutter environments. UWB signal is preferred when high resolution range measurement is required for moving targets. However, the time varying motion of flying drones may increase clutter noises in return signals and deteriorates the target detection performance, which lead to the performance degradation of anti-collision radars. We adopt a dynamic clutter suppression algorithm to estimate the time-varying distances to the moving drones with enhanced accuracy. A modified Constant False Alarm Rate(CFAR) is developed using an adaptive filter algorithm to suppress clutter while the false detection performance is well maintained. For this purpose, a velocity dependent CFAR algorithm is implemented to eliminate the clutter noise against dynamic target motions. Experiments are performed against flying drones having arbitrary trajectories to verify the performance improvement.