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UAV Positioning: From Ground to Sky

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: closed (1 December 2023) | Viewed by 11986

Special Issue Editors


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Guest Editor
School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, Northern Ireland, UK
Interests: inverse scattering; microwave imaging; ground penetrating radar; antenna measurement; unmanned aerial vehicles; positioning and geo-referring systems
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast BT7 1NN, Northern Ireland, UK
Interests: millimeterwave imaging; microwave imaging; freehand systems, ground penetrating radar; antenna measurement; unmanned aerial vehicles; positioning and geo-referring systems; RFID
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs) have become an invaluable tool for numerous remote sensing applications. Many of these applications require knowledge of the UAV position with high accuracy (e.g., airborne radar systems). Furthermore, the improvements in positioning accuracy can foster novel applications that could benefit from such enhanced positioning. The decrease in cost and convergence time of real-time kinematic (RTK) receivers has contributed to their adoption for a wide range of applications. However, as they are based on global navigation satellite systems (GNSS), they can suffer from GNSS jamming and cannot work directly indoors. Therefore, other sensors, such as depth and tracking cameras, have been increasingly used to overcome these issues.

This Special Issue aims to explore high-accuracy positioning systems for UAVs, focusing on the latest advances in both hardware and software. Application-oriented manuscripts are also encouraged, provided high-accuracy positioning is essential for the application.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Positioning sensors: GNSS, RTK, PPK (post-processing kinematic), PPP (precise point positioning); optical-based positioning; depth cameras; LIDAR (light detection and ranging); radar-based positioning.
  • Sensor fusion (e.g., IMU + RTK).
  • Indoor, outdoor, and indoor–outdoor systems.
  • Applications where high positioning accuracy is required: radar (e.g., enabling synthetic aperture radar approaches), antenna measurement, mapping, among others.

We look forward to receiving your contributions.

Dr. María García Fernández
Dr. Guillermo Álvarez-Narciandi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Remote Sensing 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 2700 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

  • unmanned aerial vehicles
  • high-accuracy positioning
  • RTK
  • GNSS
  • Depth cameras
  • LIDAR
  • sensor fusion
  • airborne radar systems
  • synthetic aperture radar
  • airborne antenna measurement systems

Published Papers (5 papers)

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Research

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21 pages, 2616 KiB  
Article
3D-SiamMask: Vision-Based Multi-Rotor Aerial-Vehicle Tracking for a Moving Object
by Mohamad Al Mdfaa, Geesara Kulathunga and Alexandr Klimchik
Remote Sens. 2022, 14(22), 5756; https://doi.org/10.3390/rs14225756 - 14 Nov 2022
Viewed by 2526
Abstract
This paper aims to develop a multi-rotor-based visual tracker for a specified moving object. Visual object-tracking algorithms for multi-rotors are challenging due to multiple issues such as occlusion, quick camera motion, and out-of-view scenarios. Hence, algorithmic changes are required for dealing with images [...] Read more.
This paper aims to develop a multi-rotor-based visual tracker for a specified moving object. Visual object-tracking algorithms for multi-rotors are challenging due to multiple issues such as occlusion, quick camera motion, and out-of-view scenarios. Hence, algorithmic changes are required for dealing with images or video sequences obtained by multi-rotors. Therefore, we propose two approaches: a generic object tracker and a class-specific tracker. Both tracking settings require the object bounding box to be selected in the first frame. As part of the later steps, the object tracker uses the updated template set and the calibrated RGBD sensor data as inputs to track the target object using a Siamese network and a machine-learning model for depth estimation. The class-specific tracker is quite similar to the generic object tracker but has an additional auxiliary object classifier. The experimental study and validation were carried out in a robot simulation environment. The simulation environment was designed to serve multiple case scenarios using Gazebo. According to the experiment results, the class-specific object tracker performed better than the generic object tracker in terms of stability and accuracy. Experiments show that the proposed generic tracker achieves promising results on three challenging datasets. Our tracker runs at approximately 36 fps on GPU. Full article
(This article belongs to the Special Issue UAV Positioning: From Ground to Sky)
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20 pages, 1132 KiB  
Article
PerDet: Machine-Learning-Based UAV GPS Spoofing Detection Using Perception Data
by Xiaomin Wei, Yao Wang and Cong Sun
Remote Sens. 2022, 14(19), 4925; https://doi.org/10.3390/rs14194925 - 01 Oct 2022
Cited by 9 | Viewed by 2803
Abstract
To ensure that unmanned aerial vehicle (UAV) positioning is not affected by GPS spoofing signals, we propose PerDet, a perception-data-based UAV GPS spoofing detection approach utilizing machine learning algorithms. Based on the principle of the position estimation process and attitude estimation [...] Read more.
To ensure that unmanned aerial vehicle (UAV) positioning is not affected by GPS spoofing signals, we propose PerDet, a perception-data-based UAV GPS spoofing detection approach utilizing machine learning algorithms. Based on the principle of the position estimation process and attitude estimation process, we choose the data gathered by the accelerometer, gyroscope, magnetometer, GPS and barometer as features. Although these sensors have different shortcomings, their variety makes sure that the selected perception data can compensate for each other. We collect the experimental data through real flights, which make PerDet more practical. Furthermore, we run various machine learning algorithms on our dataset and select the most effective classifier as the detector. Through the performance evaluation and comparison, we demonstrate that PerDet is better than existing methods and is an effective method with a detecting rate of 99.69%. For a fair comparison, we reproduce the existing method and run it on our dataset to compare the performance between this method and our PerDet approach. Full article
(This article belongs to the Special Issue UAV Positioning: From Ground to Sky)
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21 pages, 11037 KiB  
Article
Positioning of Quadruped Robot Based on Tightly Coupled LiDAR Vision Inertial Odometer
by Fangzheng Gao, Wenjun Tang, Jiacai Huang and Haiyang Chen
Remote Sens. 2022, 14(12), 2945; https://doi.org/10.3390/rs14122945 - 20 Jun 2022
Cited by 3 | Viewed by 2369
Abstract
Quadruped robots, an important class of unmanned aerial vehicles, have broad potential for applications in education, service, industry, military, and other fields. Their independent positioning plays a key role for completing assigned tasks in a complex environment. However, positioning based on global navigation [...] Read more.
Quadruped robots, an important class of unmanned aerial vehicles, have broad potential for applications in education, service, industry, military, and other fields. Their independent positioning plays a key role for completing assigned tasks in a complex environment. However, positioning based on global navigation satellite systems (GNSS) may result in GNSS jamming and quadruped robots not operating properly in environments sheltered by buildings. In this paper, a tightly coupled LiDAR vision inertial odometer (LVIO) is proposed to address the positioning inaccuracy of quadruped robots, which have poor mileage information obtained though legs and feet structures only. With this optimization method, the point cloud data obtained by 3D LiDAR, the image feature information obtained by binocular vision, and the IMU inertial data are combined to improve the precise indoor and outdoor positioning of a quadruped robot. This method reduces the errors caused by the uniform motion model in laser odometer as well as the image blur caused by rapid movements of the robot, which can lead to error-matching in a dynamic scene; at the same time, it alleviates the impact of drift on inertial measurements. Finally, the quadruped robot in the laboratory is used to build a physical platform for verification. The experimental results show that the designed LVIO effectively realizes the positioning of four groups of robots with high precision and strong robustness, both indoors or outdoors, which verify the feasibility and effectiveness of the proposed method. Full article
(This article belongs to the Special Issue UAV Positioning: From Ground to Sky)
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24 pages, 5735 KiB  
Article
Auto-Tuning of Attitude Control System for Heterogeneous Multirotor UAS
by Ayaz Ahmed Hoshu, Liuping Wang, Abdul Sattar and Alex Fisher
Remote Sens. 2022, 14(7), 1540; https://doi.org/10.3390/rs14071540 - 23 Mar 2022
Cited by 7 | Viewed by 2112
Abstract
This paper presents a heterogeneous configuration of the multirotor unmanned aerial system (UAS) that features the combined characteristics of the helicopter and quadrotor in a single multirotor design, featuring the endurance and energy efficiency similar to a helicopter, while keeping the mechanical simplicity, [...] Read more.
This paper presents a heterogeneous configuration of the multirotor unmanned aerial system (UAS) that features the combined characteristics of the helicopter and quadrotor in a single multirotor design, featuring the endurance and energy efficiency similar to a helicopter, while keeping the mechanical simplicity, control, and manoeuvrability of the standard quadrotor. Power needed for a rotorcraft to hover has the inverse relation with the rotor disc. Therefore, multiple small rotors of the quadrotor are energetically outperformed by a large rotor of the helicopter, for a similar size. Designing the stable control system for such a dynamically complex multirotor configuration remains the main challenge as the studies previously carried out on these designs have successfully demonstrated energy efficiency but at the cost of degraded attitude control. Advancements in the energetics of the multirotor results in enhanced endurance and range that could be highly effective in remote operation applications. However, a stable control system is required for accurate positioning. In this paper, a cascaded PID control approach is proposed to provide the control solution for this heterogeneous multirotor. Automatic tuning is proposed to design the PID controller for each loop of the cascade structure. A relay feedback experiment is conducted in a controlled environment, followed by identification of the open-loop frequency response and estimation of dynamics. Subsequently, PID controllers are tuned through approximated models with the help of tuning rules. A custom-designed flight controller is used to experimentally implement the proposed control structure. Presented experimental results demonstrate the efficacy of the proposed control strategy for heterogeneous multirotor UAS. Full article
(This article belongs to the Special Issue UAV Positioning: From Ground to Sky)
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Review

Jump to: Research

37 pages, 2479 KiB  
Review
Survey on Motion Planning for Multirotor Aerial Vehicles in Plan-Based Control Paradigm
by Geesara Kulathunga and Alexandr Klimchik
Remote Sens. 2023, 15(21), 5237; https://doi.org/10.3390/rs15215237 - 03 Nov 2023
Viewed by 936
Abstract
In general, optimal motion planning can be performed both locally and globally. In such a planning, the choice in favor of either local or global planning technique mainly depends on whether the environmental conditions are dynamic or static. Hence, the most adequate choice [...] Read more.
In general, optimal motion planning can be performed both locally and globally. In such a planning, the choice in favor of either local or global planning technique mainly depends on whether the environmental conditions are dynamic or static. Hence, the most adequate choice is to use local planning or local planning alongside global planning. When designing optimal motion planning, both local and global, the key metrics to bear in mind are execution time, asymptotic optimality, and quick reaction to dynamic obstacles. Such planning approaches can address the aforementioned target metrics more efficiently compared to other approaches, such as path planning followed by smoothing. Thus, the foremost objective of this study is to analyze related literature in order to understand how the motion planning problem, especially the trajectory planning problem, is formulated when being applied for generating optimal trajectories in real-time for multirotor aerial vehicles, as well as how it impacts the listed metrics. As a result of this research, the trajectory planning problem was broken down into a set of subproblems, and the lists of methods for addressing each of the problems were identified and described in detail. Subsequently, the most prominent results from 2010 to 2022 were summarized and presented in the form of a timeline. Full article
(This article belongs to the Special Issue UAV Positioning: From Ground to Sky)
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