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Advanced UAV-Based Sensor Technologies

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 40977

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Prof. Dr. Pasquale Daponte

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Department of Engineering, University of Sannio, 82100 Benevento, Italy
Interests: ADC and DAC modeling and testing; digital signal processing; distributed measurement systems; aerial photogrammetry; unmanned aerial systems (UASs); automatic test equipment for UASs
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Dr. Francesco Picariello

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Department of Engineering, University of Sannio, 82100 Benevento, Italy
Interests: electrical and electronic instrumentation; data acquisition systems (DAQs) based on compressive sampling (CS); biomedical instrumentation; distributed measurement systems, including wireless sensor networks (WSNs); Internet of Things (IoT)
Special Issues, Collections and Topics in MDPI journals

Dr. Eulalia Balestrieri

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Guest Editor

Department of Engineering, University of Sannio, 82100 Benevento, Italy
Interests: digital signal processing in telecommunications; data converter characterization; medical measurement; standardization; unmanned aerial systems (UASs)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The use of Unmanned Aerial Vehicles (UAVs), commonly known as drones, in the global civilian market is continually growing. This trend is due to the integration of high-performance processors, sensors, and electronic devices with a lower power consumption on UAV platforms. In particular, more and more sensors are being embedded on UAVs to ensure safety and automatic navigation and perform measurements during the flight according to the mission targets.

The aim of this Special Issue is to collect recent advances on sensors and sensing systems for UAV applications. High-quality research articles as well as reviews are welcome.

Of special interest is research work that seeks to address recent developments in new technology for metrology-assisted production in aerospace industry, UAV component measurement, sensors and associated signal conditioning for aerospace, and calibration methods for electronic testing and measurement for aerospace, as well as relevant prospects in terms of opportunities and challenges.

Papers are encouraged in, but not limited to, the following topics:

Electronic instrumentation for UAV;

Automatic test equipment;

Sensors and sensor systems for UAV applications;

Wireless sensor network nodes based on UAV;

Attitude and heading reference systems;

Monitoring systems;

Metrology for navigation and precise positioning;

Sensors and data fusion techniques;

Flight testing instrumentation and flight test techniques;

UAV swarms;

UAV safety and security;

Aerial-photogrammetry;

Health structural monitoring with UAV;

Precision agriculture;

Search and rescue with UAV.

Prof. Dr. Pasquale Daponte
Dr. Francesco Picariello
Dr. Eulalia Balestrieri
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

sensors
UAV
measurement uncertainty
calibration
navigation
sense and avoid
image processing
signal processing
sensor fusion
UAV testing

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Related Special Issue

Advanced UAV-Based Sensor Technologies: 2nd Edition in Sensors

Published Papers (12 papers)

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Research

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16 pages, 3731 KiB

Open AccessArticle

Direction-of-Arrival Estimation for Unmanned Aerial Vehicles and Aircraft Transponders Using a Multi-Mode Multi-Port Antenna

by Sami Alkubti Almasri, Nils L. Johannsen and Peter A. Hoeher

Sensors 2024, 24(11), 3452; https://doi.org/10.3390/s24113452 - 27 May 2024

Viewed by 830

Abstract

Increasing airspace safety is an important challenge, both for unmanned aerial vehicles (UAVs) as well as manned aircraft. Future developments of collision avoidance systems are supposed to utilize information from multiple sensing systems. A compact sensing system could employ a multi-mode multi-port antenna [...] Read more.

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PA). Their ability to radiate multiple orthogonal patterns simultaneously makes them suitable for communication applications as well as bearing and ranging applications. Furthermore, they can be designed to flexibly originate near-omnidirectional and/or directional radiation patterns. This option of flexibility with respect to the radiation characteristic is desired for antennas integrated in collision avoidance systems. Based on the aforementioned properties, M

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PAs represent a compelling option for aircraft transponders. In this paper, direction-of-arrival (DoA) estimation using an M

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PA designed for aerial applications is put to the test. First, a DoA estimation scheme suitable to be employed with M

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PAs is introduced. Next, the validity of the proposed method is confirmed through numerical simulations. Lastly, practical experiments are conducted in an antenna measurement chamber to verify the numerical results. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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19 pages, 4587 KiB

Open AccessArticle

Impact of Rainfall on the Detection Performance of Non-Contact Safety Sensors for UAVs/UGVs

by Yasushi Sumi, Bong Keun Kim, Takuya Ogure, Masato Kodama, Naoki Sakai and Masami Kobayashi

Sensors 2024, 24(9), 2713; https://doi.org/10.3390/s24092713 - 24 Apr 2024

Viewed by 992

Abstract

This study comprehensively investigates how rain and drizzle affect the object-detection performance of non-contact safety sensors, which are essential for the operation of unmanned aerial vehicles and ground vehicles in adverse weather conditions. In contrast to conventional sensor-performance evaluation based on the amount of precipitation, this paper proposes spatial transmittance and particle density as more appropriate metrics for rain environments. Through detailed experiments conducted under a variety of precipitation conditions, it is shown that sensor performance is significantly affected by the density of small raindrops rather than the total amount of precipitation. This finding challenges traditional sensor-evaluation metrics in rainfall environments and suggests a paradigm shift toward the use of spatial transmittance as a universal metric for evaluating sensor performance in rain, drizzle, and potentially other adverse weather scenarios. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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25 pages, 6335 KiB

Open AccessArticle

The Uncertainty Assessment by the Monte Carlo Analysis of NDVI Measurements Based on Multispectral UAV Imagery

by Fatemeh Khalesi, Imran Ahmed, Pasquale Daponte, Francesco Picariello, Luca De Vito and Ioan Tudosa

Sensors 2024, 24(9), 2696; https://doi.org/10.3390/s24092696 - 24 Apr 2024

Cited by 1 | Viewed by 1702

Abstract

This paper proposes a workflow to assess the uncertainty of the Normalized Difference Vegetation Index (NDVI), a critical index used in precision agriculture to determine plant health. From a metrological perspective, it is crucial to evaluate the quality of vegetation indices, which are usually obtained by processing multispectral images for measuring vegetation, soil, and environmental parameters. For this reason, it is important to assess how the NVDI measurement is affected by the camera characteristics, light environmental conditions, as well as atmospheric and seasonal/weather conditions. The proposed study investigates the impact of atmospheric conditions on solar irradiation and vegetation reflection captured by a multispectral UAV camera in the red and near-infrared bands and the variation of the nominal wavelengths of the camera in these bands. Specifically, the study examines the influence of atmospheric conditions in three scenarios: dry–clear, humid–hazy, and a combination of both. Furthermore, this investigation takes into account solar irradiance variability and the signal-to-noise ratio (SNR) of the camera. Through Monte Carlo simulations, a sensitivity analysis is carried out against each of the above-mentioned uncertainty sources and their combination. The obtained results demonstrate that the main contributors to the NVDI uncertainty are the atmospheric conditions, the nominal wavelength tolerance of the camera, and the variability of the NDVI values within the considered leaf conditions (dry and fresh). Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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20 pages, 24808 KiB

Open AccessArticle

Improvement of Tiny Object Segmentation Accuracy in Aerial Images for Asphalt Pavement Pothole Detection

by Sujong Kim, Dongmahn Seo and Soobin Jeon

Sensors 2023, 23(13), 5851; https://doi.org/10.3390/s23135851 - 24 Jun 2023

Cited by 1 | Viewed by 1641

Abstract

In this study, we propose an algorithm to improve the accuracy of tiny object segmentation for precise pothole detection on asphalt pavements. The approach comprises a three-step process: MOED, VAPOR, and Exception Processing, designed to extract pothole edges, validate the results, and manage detected abnormalities. The proposed algorithm addresses the limitations of previous methods and offers several advantages, including wider coverage. We experimentally evaluated the performance of the proposed algorithm by filming roads in various regions of South Korea using a UAV at high altitudes of 30–70 m. The results show that our algorithm outperforms previous methods in terms of instance segmentation performance for small objects such as potholes. Our study offers a practical and efficient solution for pothole detection and contributes to road safety maintenance and monitoring. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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19 pages, 10016 KiB

Open AccessArticle

Reliability Assessment of a Vision-Based Dynamic Displacement Measurement System Using an Unmanned Aerial Vehicle

by Hongjin Kim and Guyeon Kim

Sensors 2023, 23(6), 3232; https://doi.org/10.3390/s23063232 - 17 Mar 2023

Cited by 4 | Viewed by 2460

Abstract

In recent years, many studies have been conducted on the vision-based displacement measurement system using an unmanned aerial vehicle, which has been used in actual structure measurements. In this study, the dynamic measurement reliability of a vision-based displacement measurement system using an unmanned aerial vehicle was examined by measuring various vibrations with a frequency of 0 to 3 Hz and a displacement of 0 to 100 mm. Furthermore, free vibration was applied to model structures with one and two stories, and the response was measured to examine the accuracy of identifying structural dynamic characteristics. The vibration measurement results demonstrated that the vision-based displacement measurement system using an unmanned aerial vehicle has an average root mean square percentage error of 0.662% compared with the laser distance sensor in all experiments. However, the errors were relatively large in the displacement measurement of 10 mm or less regardless of the frequency. In the structure measurements, all sensors demonstrated the same mode frequency based on the accelerometer, and the damping ratios were extremely similar, except for the laser distance sensor measurement value of the two-story structure. Mode shape estimation was obtained and compared using the modal assurance criterion value compared with the accelerometer, and the values for the vision-based displacement measurement system using an unmanned aerial vehicle were close to 1. According to these results, the vision-based displacement measurement system using an unmanned aerial vehicle demonstrated results similar to those of conventional displacement sensors and can thus replace conventional displacement sensors. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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20 pages, 10993 KiB

Open AccessArticle

Assessment of Accuracy in Unmanned Aerial Vehicle (UAV) Pose Estimation with the REAL-Time Kinematic (RTK) Method on the Example of DJI Matrice 300 RTK

by Szymon Czyża, Karol Szuniewicz, Kamil Kowalczyk, Andrzej Dumalski, Michał Ogrodniczak and Łukasz Zieleniewicz

Sensors 2023, 23(4), 2092; https://doi.org/10.3390/s23042092 - 13 Feb 2023

Cited by 18 | Viewed by 4967

Abstract

The growing possibilities offered by unmanned aerial vehicles (UAV) in many areas of life, in particular in automatic data acquisition, spur the search for new methods to improve the accuracy and effectiveness of the acquired information. This study was undertaken on the assumption that modern navigation receivers equipped with real-time kinematic positioning software and integrated with UAVs can considerably improve the accuracy of photogrammetric measurements. The research hypothesis was verified during field measurements with the use of a popular Enterprise series drone. The problems associated with accurate UAV pose estimation were identified. The main aim of the study was to perform a qualitative assessment of the pose estimation accuracy of a UAV equipped with a GNSS RTK receiver. A test procedure comprising three field experiments was designed to achieve the above research goal: an analysis of the stability of absolute pose estimation when the UAV is hovering over a point, and analyses of UAV pose estimation during flight along a predefined trajectory and during continuous flight without waypoints. The tests were conducted in a designated research area. The results were verified based on direct tachometric measurements. The qualitative assessment was performed with the use of statistical methods. The study demonstrated that in a state of apparent stability, horizontal deviations of around 0.02 m occurred at low altitudes and increased with a rise in altitude. Mission type significantly influences pose estimation accuracy over waypoints. The results were used to verify the accuracy of the UAV’s pose estimation and to identify factors that affect the pose estimation accuracy of an UAV equipped with a GNSS RTK receiver. The present findings provide valuable input for developing a new method to improve the accuracy of measurements performed with the use of UAVs. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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14 pages, 4456 KiB

Open AccessArticle

Near Real-Time Volumetric Estimates Using Unmanned Aerial Platforms Equipped with Depth and Tracking Sensors

by Donato Amitrano, Luca Cicala, Giovanni Cuciniello, Marco De Mizio, Mariana Poderico and Francesco Tufano

Sensors 2022, 22(23), 9462; https://doi.org/10.3390/s22239462 - 3 Dec 2022

Cited by 3 | Viewed by 1781

Abstract

Volume estimation of specific objects via close-range remote sensing is a complex task requiring expensive hardware and/or significant computational burden, often discouraging users potentially interested in the technology. This paper presents an innovative system for cost-effective near real-time volume estimation based on a custom platform equipped with depth and tracking cameras. Its performance has been tested in different application-oriented scenarios and compared against measurements and state-of-the-art photogrammetry. The comparison showed that the developed architecture is able to provide estimates fully comparable with the benchmark, resulting in a quick, reliable and cost-effective solution to the problem of volumetric estimates within the functioning range of the exploited sensors. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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25 pages, 5116 KiB

Open AccessArticle

Development and Calibration of Pressure-Temperature-Humidity (PTH) Probes for Distributed Atmospheric Monitoring Using Unmanned Aircraft Systems

by Karla S. Ladino, Michael P. Sama and Victoria L. Stanton

Sensors 2022, 22(9), 3261; https://doi.org/10.3390/s22093261 - 24 Apr 2022

Cited by 3 | Viewed by 2793

Abstract

Small unmanned aircraft systems (UAS) are increasingly being used for meteorology and atmospheric monitoring. The ease of deployment makes distributed sensing of parameters such as barometric pressure, temperature, and relative humidity in the lower atmospheric boundary layer feasible. However, constraints on payload size and weight, and to a lesser extent power, limit the types of sensors that can be deployed. The objective of this work was to develop a miniature pressure-temperature-humidity (PTH) probe for UAS integration. A set of eight PTH probes were fabricated and calibrated/validated using an environmental chamber. An automated routine was developed to facilitate calibration and validation from a large set of temperature and relative humidity setpoints. Linear regression was used to apply temperature and relative humidity calibrations. Barometric pressure was calibrated using a 1-point method consisting of an offset. The resulting PTH probes were less than 4 g in mass and consumed less than 1 mA when operated from a 5 VDC source. Measurements were transmitted as a formatted string in ASCII format at 1 Hz over a 3.3 V TTL UART. Prior to calibration, measurements between individual PTH probes were significantly different. After calibration, no significant differences in temperature measurements across all PTH probes were observed, and the level of significance between PTH probes was reduced. Actual differences between calibrated PTH probes were likely to be negligible for most UAS-based applications, regardless of significance. RMSE across all calibrated PTH probes for the pressure, temperature, and relative humidity was less than 31 Pa, 0.13 °C, and 0.8% RH, respectively. The resulting calibrated PTH probes will improve the ability to quantify small variations in ambient conditions during coordinated multi-UAS flights. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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23 pages, 13457 KiB

Open AccessArticle

Extraction of a Weak Flow Field for a Multi-Rotor Unmanned Aerial Vehicle (UAV) Using High-Speed Background-Oriented Schlieren (BOS) Technology

by Xianglei Liu, Tongxin Guo, Pengfei Zhang, Zhenkai Jia and Xiaohua Tong

Sensors 2022, 22(1), 43; https://doi.org/10.3390/s22010043 - 22 Dec 2021

Cited by 2 | Viewed by 3157

Abstract

To optically capture and analyze the structure and changes of the flow field of a weak airflow object with high accuracy, this study proposes novel weak flow field extraction methods based on background-oriented schlieren. First, a fine background pattern texture and a sensor network layout were designed to satisfy the requirement of weak flow field extraction. Second, the image displacement was extracted by calculating the correlation matrix in the frequency domain for a particle image velocimetry algorithm, and further calculations were performed for the density field using Poisson’s equation. Finally, the time series baseline stacking method was proposed to obtain the flow field changes of weak airflow structures. A combustion experiment was conducted to validate the feasibility and accuracy of the proposed method. The results of a quad-rotor unmanned aerial vehicle experiment showed that the clear, uneven, and continuous quantitative laminar flow field could be obtained directly, which overcame the interference of the weak airflow, large field of view, and asymmetrical steady flow. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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18 pages, 3894 KiB

Open AccessArticle

Localization System for Lightweight Unmanned Aerial Vehicles in Inspection Tasks

by Diego Benjumea, Alfonso Alcántara, Agustin Ramos, Arturo Torres-Gonzalez, Pedro Sánchez-Cuevas, Jesus Capitan, Guillermo Heredia and Anibal Ollero

Sensors 2021, 21(17), 5937; https://doi.org/10.3390/s21175937 - 3 Sep 2021

Cited by 8 | Viewed by 3040

Abstract

This paper presents a localization system for Unmanned Aerial Vehicles (UAVs) especially designed to be used in infrastructure inspection, where the UAVs have to fly in challenging conditions, such as relatively high altitude (e.g., 15 m), eventually with poor or absent GNSS (Global Navigation Satellite System) signal reception, or the need for a BVLOS (Beyond Visual Line of Sight) operation in some periods. In addition, these infrastructure inspection applications impose the following requirements for the localization system: defect traceability, accuracy, reliability, and fault tolerance. Our system proposes a lightweight solution combining multiple stereo cameras with a robotic total station to comply with these requirements, providing full-state estimation (i.e., position, orientation, and linear and angular velocities) in a fixed and time-persistent reference frame. Moreover, the system can align and fuse all sensor measurements in real-time at high frequency. We have integrated this localization system in our aerial platform, and we have tested its performance for inspection in a real-world viaduct scenario, where the UAV has to operate with poor or absent GNSS signal at high altitude. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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Review

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25 pages, 3424 KiB

Open AccessReview

Review of Sensor Technology to Support Automated Air-to-Air Refueling of a Probe Configured Uncrewed Aircraft

by Jonathon Parry and Sarah Hubbard

Sensors 2023, 23(2), 995; https://doi.org/10.3390/s23020995 - 15 Jan 2023

Cited by 14 | Viewed by 6138

Abstract

As technologies advance and applications for uncrewed aircraft increase, the capability to conduct automated air-to-air refueling becomes increasingly important. This paper provides a review of required sensors to enable automated air-to-air refueling for an uncrewed aircraft, as well as a review of published research on the topic. Automated air-to-air refueling of uncrewed aircraft eliminates the need for ground infrastructure for intermediate refueling, as well as the need for on-site personnel. Automated air-to-air refueling potentially supports civilian applications such as weather monitoring, surveillance for wildfires, search and rescue, and emergency response, especially when airfields are not available due to natural disasters. For military applications, to enable the Air Wing of the Future to strike at the ranges required for the mission, both crewed and uncrewed aircraft must be capable of air-to-air refueling. To cover the sensors required to complete automated air-to-air refueling, a brief history of air-to-air refueling is presented, followed by a concept of employment for uncrewed aircraft refueling, and finally, a review of the sensors required to complete the different phases of automated air-to-air refueling. To complete uncrewed aircraft refueling, the uncrewed receiver aircraft must have the sensors required to establish communication, determine relative position, decrease separation to astern position, transition to computer vision, position keep during refueling, and separate from the tanker aircraft upon completion of refueling. This paper provides a review of the twelve sensors that would enable the uncrewed aircraft to complete the seven tasks required for automated air-to-air refueling. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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34 pages, 2959 KiB

Open AccessEditor’s ChoiceReview

Sensors and Measurements for UAV Safety: An Overview

by Eulalia Balestrieri, Pasquale Daponte, Luca De Vito, Francesco Picariello and Ioan Tudosa

Sensors 2021, 21(24), 8253; https://doi.org/10.3390/s21248253 - 10 Dec 2021

Cited by 45 | Viewed by 8935

Abstract

Unmanned aerial vehicles’ (UAVs) safety has gained great research interest due to the increase in the number of UAVs in circulation and their applications, which has inevitably also led to an increase in the number of accidents in which these vehicles are involved. The paper presents a classification of UAV safety solutions that can be found in the scientific literature, putting in evidence the fundamental and critical role of sensors and measurements in the field. Proposals from research on each proposed class concerning flight test procedures, in-flight solutions including soft propeller use, fault and damage detection, collision avoidance and safe landing, as well as ground solution including testing and injury and damage quantification measurements are discussed. Full article

(This article belongs to the Special Issue Advanced UAV-Based Sensor Technologies)

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