An Overview on Down-Looking UAV-Based GPR Systems

Noviello, Carlo; Gennarelli, Gianluca; Esposito, Giuseppe; Ludeno, Giovanni; Fasano, Giancarmine; Capozzoli, Luigi; Soldovieri, Francesco; Catapano, Ilaria

doi:10.3390/rs14143245

Cited by 28 publications

(11 citation statements)

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“…Research in this domain has explored various methodologies, including sensor fusion, the use of Inertial Measurement Units (IMUs), and image-based inference techniques. Notably, image-based navigation employs multiple strategies for location estimation, such as recognizing environmental landmarks and analyzing optical flow [4][5][6][7]. However, these image-based methods typically demand extensive computational resources due to their reliance on intricate image processing pipelines.…”

Section: Introductionmentioning

confidence: 99%

SiaN-VO: Siamese Network for Visual Odometry

Faiçal,

Marcondes,

Verri

2024

Sensors

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Despite the significant advancements in drone sensory device reliability, data integrity from these devices remains critical in securing successful flight plans. A notable issue is the vulnerability of GNSS to jamming attacks or signal loss from satellites, potentially leading to incomplete drone flight plans. To address this, we introduce SiaN-VO, a Siamese neural network designed for visual odometry prediction in such challenging scenarios. Our preliminary studies have shown promising results, particularly for flights under static conditions (constant speed and altitude); while these findings are encouraging, they do not fully represent the complexities of real-world flight conditions. Therefore, in this paper, we have furthered our research to enhance SiaN-VO, improving data integration from multiple sensors and enabling more accurate displacement predictions in dynamic flight conditions, thereby marking a significant step forward in drone navigation technology.

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Section: Introductionmentioning

confidence: 99%

SiaN-VO: Siamese Network for Visual Odometry

Faiçal,

Marcondes,

Verri

2024

Sensors

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“…Experimental examples concerning different types of contactless GPRs are presented to validate the effectiveness of MWT when combined with signal-filtering procedures. Noviello et al [15] presented a comprehensive review of the current status and…”

Section: Introductionmentioning

confidence: 99%

Drone direction estimation: phase method with two-channel direction finder

Kozhabayeva,

Yerzhan,

Boykachev

et al. 2024

IJECE

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This scientific article presents a block diagram of a two-channel radio direction finder that effectively uses the phase method to determine the direction of the signal source. The main attention is paid to the mathematical model of the formation of the cardioid radiation pattern of biconical antennas, which have unique directivity characteristics. These features significantly affect the accuracy and reliability of the bearing determination process. The developed algorithm aims to accurately determine the direction of motion of an unmanned aerial vehicle, especially in the context of a two-channel radio receiver and a five-element antenna system. This antenna system provides unique capabilities for increased resolution and directional accuracy. The article also touches on the issue of software implementation of the developed algorithm, which is aimed at increasing the number of generated bearing estimates in conditions of limited time for observing an unmanned aerial vehicle. Thus, the proposed method is of interest in the field of precision direction finding in the context of small unmanned vehicles.

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“…Ground Penetrating Radar (GPR) is worthy of consideration in this context. However, current commercially available GPR systems have limitations in their ability to inspect vertical structures and are difficult to use on moving platforms such as mini-Unmanned Aerial Vehicles (UAVs) [1]. This paper presents a new prototype imagined for non-destructive inspections of elongated, horizontal, and vertical structures using a compact and lightweight GPR.…”

Section: Introductionmentioning

confidence: 99%

UAV‐based GPR prototype for structural monitoring of bridges: preliminary results and perspectives

Esposito,

Salari,

Catapano

et al. 2023

ce papers

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Structural Health Monitoring (SHM) is a challenging task requiring novel inspection paradigms and methodological tools devoted to support effective and timely maintenance actions. In this context, non‐destructive technologies (NDTs) turn out to be of paramount importance and Ground Penetrating Radar (GPR) is worthy of consideration for on‐demand, high‐resolution, subsurface surveys. Although GPR is an assessed technology, commercially available systems mainly work close to the structure under test, and those suitable to be mounted on moving platforms are hard to be used for the inspection of vertical structures. In this frame, mini–Unmanned Aerial Vehicles (UAVs) equipped with radar systems are worthy of consideration because of their potential advantages in terms of versatility. This paper deals with the design of a compact mini‐drone‐based radar prototype for contactless imaging of elongated, horizontal and vertical structures. Herein, the design guidelines are discussed qualitatively and the assembled prototype is presented. Moreover, a performance analysis is provided by accounting for simulated data and preliminary experiments carried out in controlled conditions. Conclusions analyze challenges and perspectives.

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An Overview on Down-Looking UAV-Based GPR Systems

Cited by 28 publications

References 50 publications

SiaN-VO: Siamese Network for Visual Odometry

SiaN-VO: Siamese Network for Visual Odometry

Drone direction estimation: phase method with two-channel direction finder

UAV‐based GPR prototype for structural monitoring of bridges: preliminary results and perspectives

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