A Review of Counter-UAS Technologies for Cooperative Defensive Teams of Drones

Castrillo, Vittorio Ugo; Manco, Angelo; Pascarella, Domenico; Gigante, Gabriella

doi:10.3390/drones6030065

Cited by 58 publications

(32 citation statements)

References 80 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Instead, reference [30] discusses a resilience action plan for airport stakeholders to defend an airport against airborne threats from misused drones. Lastly, several works provide a detailed analysis of the technological options for counter-drone systems, e.g., [30][31][32]. Thus, our proposed work represents the first attempt at defining a joint data-driven and model-based methodological framework for the risk assessment of airport drone intrusions, considering both safety and security perspectives.…”

Section: Security Incidentmentioning

confidence: 99%

A Methodological Framework for the Risk Assessment of Drone Intrusions in Airports

et al. 2022

Self Cite

View full text Add to dashboard Cite

Drone expansion needs to be considered as a menace in cases of negligent, illicit, or non-cooperative use. In the case of airports, a complete protection against drone intrusion should rely on an intrusion management system, aiming at avoiding the closure of the airport. This system requires the setting of proper risk assessment methodologies for airport operations, to explicitly consider the features of drone intrusion, possibly from a quantitative point of view. This work proposes a methodological framework for the risk assessment of drone intrusions in airports, tailored on drone-intrusion features, airport features, and current operations, and considering both safety-related and security-related causes. The framework is based on the combination of model-based and data-driven approaches in order to: (i) estimate an airport vulnerability index, to measure the susceptibility of the airport to drone intrusions, based on reference datasets; (ii) specify a set of event trees to evaluate the risks of the different threat scenarios related to drone intrusions. The proposed methodological framework is applied to a concrete case study, related to Milan Malpensa airport. The achieved results show the effectiveness of the approach and elicit further requirements for counter-drone systems in airports based on the assessed risks.

show abstract

Section: Security Incidentmentioning

confidence: 99%

A Methodological Framework for the Risk Assessment of Drone Intrusions in Airports

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Such invasions are carried out through unauthorized access to restricted areas. According to the United States Federal Aviation Authority (FAA), there were 8344 drone-related violations between 2016 and 2019 [ 10 ] despite available counter-invasive technologies. Furthermore, there are already instances of invasions employing quad-copter UAVs (such as the DJI Phantom) for recreational, logistics, and consumer use to destroy industrial sites, transport dangerous goods over borders, and assault important installations [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, due to its inherent shortcomings, using a single detection method to accomplish this purpose is ineffective. Moreover, the majority of neutralization techniques are either manual, militaristic, or reactive [ 10 , 16 , 17 ]. Undoubtedly, improper neutralization of invasive drones in a DTN, incorrect visual recognition of conveyed objects, and late or inaccurate detection can harm the future of DTS.…”

Section: Introductionmentioning

confidence: 99%

ALIEN: Assisted Learning Invasive Encroachment Neutralization for Secured Drone Transportation System

Ajakwe

Ihekoronye

Kim

et al. 2023

Sensors

View full text Add to dashboard Cite

Priority-based logistics and the polarization of drones in civil aviation will cause an extraordinary disturbance in the ecosystem of future airborne intelligent transportation networks. A dynamic invention needs dynamic sophistication for sustainability and security to prevent abusive use. Trustworthy and dependable designs can provide accurate risk assessment of autonomous aerial vehicles. Using deep neural networks and related technologies, this study proposes an artificial intelligence (AI) collaborative surveillance strategy for identifying, verifying, validating, and responding to malicious use of drones in a drone transportation network. The dataset for simulation consists of 3600 samples of 9 distinct conveyed objects and 7200 samples of the visioDECT dataset obtained from 6 different drone types flown under 3 different climatic circumstances (evening, cloudy, and sunny) at different locations, altitudes, and distance. The ALIEN model clearly demonstrates high rationality across all metrics, with an F1-score of 99.8%, efficiency with the lowest noise/error value of 0.037, throughput of 16.4 Gbps, latency of 0.021, and reliability of 99.9% better than other SOTA models, making it a suitable, proactive, and real-time avionic vehicular technology enabler for sustainable and secured DTS.

show abstract

“…They can also be used to smuggle illicit goods, such as drugs [4], or even be utilized as weapons by terrorists. As experience in the Ukraine conflict shows, UAVs are actively implemented by both sides in military operations, and neutralization of UAVs is especially relevant [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…There are many means of UAV detection and neutralization There are four main technologies of detection: optical in various bands [8,9]; passive acoustic [10]; passive radio-receiving emitted radio radiation from the UAV [11]; and active radio-using radars [12]. The possibilities for neutralizing the detected drones are examined in [6,13,14]. Nonetheless, all of them have some disadvantages.…”

Section: Introductionmentioning

confidence: 99%

Hostile UAV Detection and Neutralization Using a UAV System

Rudys

Laučys

Ragulis

et al. 2022

Drones

View full text Add to dashboard Cite

The technologies of Unmanned Aerial Vehicles (UAVs) have seen extremely rapid development in recent years. UAV technologies are being developed much faster than the means of their legislation. There have been many means of UAV detection and neutralization proposed in recent research; nonetheless, all of them have serious disadvantages. The essential problems in the detection of UAVs is the small size of UAVs, weak radio wave reflection, weak radio signal, and sound emitting. The main problem of conventional UAV countermeasures is the short detection and neutralization range. The authors propose the concept of the airborne counter-UAV platform (consisting of several vehicles) with radar. We use a low-cost marine radar with a high resolution 2 m wide antenna, embedded into the wing. Radar scanning is implemented by changing the heading of the aircraft. For the countermeasures, the authors suggest using a small rotorcraft UAV carried by a bigger fixed-wing one. A mathematical model that allows the calculation of the coordinates of the detected drone while scanning the environment in a moving UAV with radar was created. Furthermore, the results of integrated radar performance with a detected drone and the results of successful neutralization experiments of different UAVs were achieved.

show abstract

A Review of Counter-UAS Technologies for Cooperative Defensive Teams of Drones

Cited by 58 publications

References 80 publications

A Methodological Framework for the Risk Assessment of Drone Intrusions in Airports

A Methodological Framework for the Risk Assessment of Drone Intrusions in Airports

ALIEN: Assisted Learning Invasive Encroachment Neutralization for Secured Drone Transportation System

Hostile UAV Detection and Neutralization Using a UAV System

Contact Info

Product

Resources

About