Comprehensive Review of UAV Detection, Security, and Communication Advancements to Prevent Threats

Abro, Ghulam E Mustafa; Zulkifli, Saiful A.; Masood, Rana Javed; Asirvadam, Vijanth S.; Laouti, Anis

doi:10.3390/drones6100284

Cited by 53 publications

(42 citation statements)

References 77 publications

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“…However, during long-time flight, the accumulated error of inertial navigation cannot be ignored. Besides, because of huge advancements in the technology, UAVs has a high probability of experiencing attacks such as GPS spoofing [49]. Celestial and inertial integrated navigation system applied to UAVs is a topic of interest, which is a good alternative to GPS [50].…”

Section: B Potential Applicationsmentioning

confidence: 99%

An All-Day Attitude Sensor Integrating Stars and Sun Measurement Based on Extended Pixel Response of CMOS APS Imager

Cao

Zhan

et al. 2023

IEEE Trans. Instrum. Meas.

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For celestial measurement, it is difficult to enable a single optical system to image and measure both stars and the sun due to vastly different light intensity of targets and limited response capability of the image sensor pixel. Here, we develop an all-day optical attitude sensor integrating stars and the sun measurement based on extended pixel response model of the CMOS APS (Active-pixel sensor) imager. For extremely large light intensity, we extend the conventional pixel response model to the oversaturated stage where the pixel values reverse and drop below the saturation value. Based on this, the integration of the star sensor and the sun sensor is realized. The pixels image the starry sky with linear response, and make use of the oversaturation response to image the sun and obtain a black spot on the bright background. This principle enables the capability of all-day high-precision attitude measurement using a single miniaturized sensor. An integrated optical attitude sensor is designed and manufactured. Ground-based observation results show that the orientation accuracy from sun measurement is better than 9" (3σ), and the attitude accuracy from star measurement is better than 5" (3σ) for pointing and 11" (3σ) for rolling. The sensor can be applied to high-precision all-day navigation systems for miniaturized spacecrafts and aircrafts.

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Section: B Potential Applicationsmentioning

confidence: 99%

An All-Day Attitude Sensor Integrating Stars and Sun Measurement Based on Extended Pixel Response of CMOS APS Imager

Cao

Zhan

et al. 2023

IEEE Trans. Instrum. Meas.

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“…The maintenance and security of drone transportation present a variety of surveillance issues due to the continued advancement of the drones’ underlying technology [ 1 , 20 ]. To conduct drone surveillance, it is necessary to communicate with, identify, authenticate, elicit, and disarm drones considered dangerous from a drone pool in a DTN.…”

Section: Overview Of Invasive Drone Encroachment Techniquesmentioning

confidence: 99%

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

Ajakwe

Ihekoronye

Kim

et al. 2023

Sensors

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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.

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“…A disaster situation in [ 30 ] incorporates 2D UAV placement in the presence of critical nodes, whereas the efficiency in UAV networks highly depends on LoS/NLoS probabilities and elevation-demanding 3D optimization. A secondary critical challenge in certain emergency networks is to secure this communication link as discussed in [ 31 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

On Coverage of Critical Nodes in UAV-Assisted Emergency Networks

Waheed

Ahmad

Ahmed

et al. 2023

Sensors

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Unmanned aerial vehicle (UAV)-assisted networks ensure agile and flexible solutions based on the inherent attributes of mobility and altitude adaptation. These features render them suitable for emergency search and rescue operations. Emergency networks (ENs) differ from conventional networks. They often encounter nodes with vital information, i.e., critical nodes (CNs). The efficacy of search and rescue operations highly depends on the eminent coverage of critical nodes to retrieve crucial data. In a UAV-assisted EN, the information delivery from these critical nodes can be ensured through quality-of-service (QoS) guarantees, such as capacity and age of information (AoI). In this work, optimized UAV placement for critical nodes in emergency networks is studied. Two different optimization problems, namely capacity maximization and age of information minimization, are formulated based on the nature of node criticality. Capacity maximization provides general QoS enhancement for critical nodes, whereas AoI is focused on nodes carrying critical information. Simulations carried out in this paper aim to find the optimal placement for each problem based on a two-step approach. At first, the disaster region is partitioned based on CNs’ aggregation. Reinforcement learning (RL) is then applied to observe optimal placement. Finally, network coverage over optimal UAV(s) placement is studied for two scenarios, i.e., network-centric and user-centric. In addition to providing coverage to critical nodes, the proposed scheme also ensures maximum coverage for all on-scene available devices (OSAs).

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Comprehensive Review of UAV Detection, Security, and Communication Advancements to Prevent Threats

Cited by 53 publications

References 77 publications

An All-Day Attitude Sensor Integrating Stars and Sun Measurement Based on Extended Pixel Response of CMOS APS Imager

An All-Day Attitude Sensor Integrating Stars and Sun Measurement Based on Extended Pixel Response of CMOS APS Imager

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

On Coverage of Critical Nodes in UAV-Assisted Emergency Networks

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