Multi-Agent System for Rogue Drone Interception

Souli, Nicolas; Kolios, Panayiotis; Ellinas, Georgios

doi:10.1109/lra.2023.3245412

Cited by 9 publications

(5 citation statements)

References 33 publications

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“…Intercepting and analyzing communication signals between the drone and its operator can provide insights into the drone's mission and enable countermeasures [102]. This can be done to gather intelligence, track the drone's movements, or even take control of the UAV.…”

Section: Communication Signal Interception (Soft Kill)mentioning

confidence: 99%

Counter Drone Technology: A Review

Gonzalez-Jorge,

Aldao,

Fontenla-Carrera

et al. 2024

Preprint

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Unmanned Aerial Vehicles (UAVs), commonly known as drones, have experienced a significant surge in both civilian and military applications, owing to their versatility and cost-effectiveness. However, a negligent use or the operation with harmful intent of these aircraft poses a potential risk to public safety and the privacy of individuals. In response to this threat, counter-drone systems have been developed in recent years, including technologies to detect, position, and neutralize these aircraft. This paper presents a review of different existing commercial counter-drone systems, the technologies behind detection, tracking, and classification, as well as soft and hard kill mitigation.

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Section: Communication Signal Interception (Soft Kill)mentioning

confidence: 99%

Counter Drone Technology: A Review

Gonzalez-Jorge,

Aldao,

Fontenla-Carrera

et al. 2024

Preprint

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“…Jamming the signal of the drones [19,20] is a possible way of countering drone attacks (Table 2). Jamming devices work by emitting electromagnetic noise at radio frequencies that drones operate and transmit videos at.…”

Section: Drone Jammersmentioning

confidence: 99%

Drones are Endangering Energy Critical Infrastructure, and How We Can Deal with This

Kootala,

Mousa,

Pong

2023

Energies

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Drones are becoming a greater threat to modern electrical grids with the capability to cause expensive and time-consuming damage repairs to substations and transmission lines. Consumer drones have the potential to cause harm at a low cost, and finding methods to counter these threats is becoming more crucial to keep grids secure. In 2021, there was an attempted attack on a substation with a consumer drone which highlighted the need for research in this area. Previously, there has been a large focus on counter drones around places such as airports; however, more focus is warranted to analyze drone impact on the grid infrastructure. Methods to counter drones’ harmful impacts vary from physical methods to using electromagnetic waves. This article looks to identify and propose potential applications for existing technologies, as well as developing anti-drone technologies. These methods have not been adopted yet; thus, there is a great opportunity to utilize these existing technologies to defend the grid. The methods investigated were surveillance cameras, patrolling drones, nets, signal jammers, and energy weapons. The existing technology is currently lacking in the area of drone defense and can be improved with existing studies. However, there is a need to identify those methods and find ways to apply them to the power grid. Different defending technologies vary concerning their potential implementation. This paper also identifies and categorizes different results these methods produce to counter drones and their associated costs.

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“…Aiming at the problem of high dimensionality and high dynamics in the cluster confrontation game, an evolution strategies optimization method was proposed [6]. To deal with the major threat to public safety, as well as critical 2 of 22 infrastructure security caused by unmanned aircraft vehicles, a multi-agent jamming system was presented [7].…”

Section: Introductionmentioning

confidence: 99%

Accelerating Fuzzy Actor–Critic Learning via Suboptimal Knowledge for a Multi-Agent Tracking Problem

Wang

Mao

et al. 2023

Electronics

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Multi-agent differential games usually include tracking policies and escaping policies. To obtain the proper policies in unknown environments, agents can learn through reinforcement learning. This typically requires a large amount of interaction with the environment, which is time-consuming and inefficient. However, if one can obtain an estimated model based on some prior knowledge, the control policy can be obtained based on suboptimal knowledge. Although there exists an error between the estimated model and the environment, the suboptimal guided policy will avoid unnecessary exploration; thus, the learning process can be significantly accelerated. Facing the problem of tracking policy optimization for multiple pursuers, this study proposed a new form of fuzzy actor–critic learning algorithm based on suboptimal knowledge (SK-FACL). In the SK-FACL, the information about the environment that can be obtained is abstracted as an estimated model, and the suboptimal guided policy is calculated based on the Apollonius circle. The guided policy is combined with the fuzzy actor–critic learning algorithm, improving the learning efficiency. Considering the ground game of two pursuers and one evader, the experimental results verified the advantages of the SK-FACL in reducing tracking error, adapting model error and adapting to sudden changes made by the evader compared with pure knowledge control and the pure fuzzy actor–critic learning algorithm.

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Multi-Agent System for Rogue Drone Interception

Cited by 9 publications

References 33 publications

Counter Drone Technology: A Review

Counter Drone Technology: A Review

Drones are Endangering Energy Critical Infrastructure, and How We Can Deal with This

Accelerating Fuzzy Actor–Critic Learning via Suboptimal Knowledge for a Multi-Agent Tracking Problem

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