Modelling, Control and Emerging Application for Unmanned Vehicles

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 8895

Special Issue Editors

College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: seamless positioning and navigation in challenging environments
Special Issues, Collections and Topics in MDPI journals
School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
Interests: computer vision; machine learning; multi-sensor integration and robot autonomous navigation technology

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Guest Editor
1. College of Information Technology, United Arab Emirates University, Abu Dhabi 15551, United Arab Emirates
2. Network and Mobility Competence Center at DAI Labor, Technical University of Berlin, Berlin, Germany
Interests: machine learning; autonomous driving; future mobile networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

In recent years, unmanned vehicles (including ground and aerial vehicles) have been developing as a strategic solution in many fields, such as logistics, intelligent transport systems (ITS), and intelligent surveillance. Successful operation of unmanned vehicles relies on a combination of the following: (1) PNT, such as global navigation satellite systems (GNSS), dead reckoning sensors (e.g., inertial measurement units, odometers, and magnetometers), and signals of opportunity; (2) remote and environmental sensors, such as cameras, LiDAR, RADAR, and ultrasonic sensors; (3) spatial databases, such as 3D city models; (4) models and algorithms to collate and interpret the multisensor data; (5) powerful processors to execute algorithms for the real-time planning of safe paths forward; (6) accurate, robust, and adaptive algorithms and reliable hardware to control vehicle driving behavior; (7) integrity monitoring for the system, including all the aforementioned software and hardware. The integration of these factors enhances the overall performance of unmanned vehicles, especially in challenging environments (such as tunnels, urban centers, underground parking, etc.).

While unmanned vehicles are critical in many fields, further attention should be paid to research identifying the requirements of unmanned vehicles, and the technologies necessary for the delivery of those requirements. The aim of this Special Issue is to bring together relevant research and researchers to begin to address these important issues. This Special Issue seeks to consolidate past research and chart future research directions. It is within this context that we invite you to contribute to this Special Issue: “Modelling, Control, and Emerging Applications for Unmanned Vehicles”.

The topics of interests include, but are not limited to, the following:

  • Applications and requirements for unmanned vehicles;
  • Receiver/sensor/antenna design technologies;
  • Unmanned-vehicle-assisted 5G/6G-and-beyond communications;
  • Multisource cooperative positioning methods in complex environments;
  • Measurements/observables processing models (including error mitigation);
  • System/sensor/spatial data integration or data fusion, and applications, with a particular focus on very high performance as measured in terms of the required navigation performance parameters of accuracy, integrity, continuity, and availability;
  • Errors and their modelling;
  • Interference (jamming, meaconing, and spoofing) and integrity/quality monitoring;
  • Advanced analytics (e.g., AI-based applications);
  • Edge-computing-assisted high-performance localization;
  • Path planning and optimizing strategies;
  • Computer vision;
  • Controlling techniques.

Technical Program Committee Members:

  1. Mr. Qi Cheng  The Hong Kong Polytechnic University

Dr. Rui Sun
Dr. Fei Xie
Dr. Manzoor Ahmed Khan
Guest Editors

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Keywords

  • navigation
  • controlling models
  • integrity monitoring
  • computer vision
  • 5G/6G communication

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Published Papers (3 papers)

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Research

13 pages, 5985 KiB  
Article
Optimal GPS Acquisition Algorithm in Severe Ionospheric Scintillation Scene
by Mengying Lin, Yimei Luo, Xuefen Zhu, Gangyi Tu and Zhengpeng Lu
Electronics 2023, 12(6), 1343; https://doi.org/10.3390/electronics12061343 - 12 Mar 2023
Cited by 2 | Viewed by 1712
Abstract
The Global Positioning System (GPS) plays an important role in navigation and positioning services. When GPS signals propagate through a complex space environment, they are susceptible to interference of ionospheric scintillation. As one of the biggest interference sources on GPS navigation and positioning, [...] Read more.
The Global Positioning System (GPS) plays an important role in navigation and positioning services. When GPS signals propagate through a complex space environment, they are susceptible to interference of ionospheric scintillation. As one of the biggest interference sources on GPS navigation and positioning, ionospheric scintillation will lead to signal intensity decline and carrier phase fluctuation, making signal acquisition of the GPS receiver challenging. Thus, an acquisition algorithm based on differential coherent integration combining accumulation correlation and bit sign transition estimation is proposed. The coherent accumulation is applied to reduce computational loads and contribution by the Gaussian white noise in the signal. Moreover, the differential coherence integration is utilized to eliminate data blocks with bit transition, prolonging the coherence integration time and improving the data utilization rate. Experimental results show that under severe ionospheric scintillation condition, weak GPS signals can be acquired successfully after improving the acquisition algorithm, with the acquisition probability reaching 50% when the signal-to-interference ratio (SIR) drops to −34 dB. Comparing to the differential coherence integration, the complexity of the calculation reduces to only 21.75% effectively after the improvement. The execution time is less than half of the differential coherence integral. Full article
(This article belongs to the Special Issue Modelling, Control and Emerging Application for Unmanned Vehicles)
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15 pages, 1186 KiB  
Article
Implanting Intelligence in 5G Mobile Networks—A Practical Approach
by Sumbal Malik, Manzoor Ahmed Khan, Aadam, Hesham El-Sayed, Jalal Khan and Obaid Ullah
Electronics 2022, 11(23), 3933; https://doi.org/10.3390/electronics11233933 - 28 Nov 2022
Cited by 1 | Viewed by 2795
Abstract
With the advancement in various technological fronts, we are expecting the design goals of smart cities to be realized earlier than expected. Undoubtedly, communication networks play the crucial role of backbone to all the verticals of smart cities, which is why we are [...] Read more.
With the advancement in various technological fronts, we are expecting the design goals of smart cities to be realized earlier than expected. Undoubtedly, communication networks play the crucial role of backbone to all the verticals of smart cities, which is why we are surrounded by terminologies such as the Internet of Things, the Internet of Vehicles, the Internet of Medical Things, etc. In this paper, we focus on implanting intelligence in 5G and beyond mobile networks. In this connection, we design and develop a novel data-driven predictive model which may serve as an intelligent slicing framework for different verticals of smart cities. The proposed model is trained on different machine learning algorithms to predict the optimal network slice for a requested service resultantly assisting in allocating enough resources to the slice based on the traffic prediction. Full article
(This article belongs to the Special Issue Modelling, Control and Emerging Application for Unmanned Vehicles)
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18 pages, 9823 KiB  
Article
A Novel Airspace Planning Algorithm for Cooperative Target Localization
by Yi Mao, Yongwen Zhu, Zhili Tang and Zhijie Chen
Electronics 2022, 11(18), 2950; https://doi.org/10.3390/electronics11182950 - 17 Sep 2022
Cited by 67 | Viewed by 3817
Abstract
With the development of modern electromagnetic stealth technology and ARM, traditional active radar detection cannot accomplish its detection mission, limited by its ability. Relying on such superior advantages such as imperceptibility, anti-electromagnetic interference and electromagnetic stealth, passive transducers are playing an indispensable and [...] Read more.
With the development of modern electromagnetic stealth technology and ARM, traditional active radar detection cannot accomplish its detection mission, limited by its ability. Relying on such superior advantages such as imperceptibility, anti-electromagnetic interference and electromagnetic stealth, passive transducers are playing an indispensable and significant role in situation awareness. While, in addition to different passive transducer localization modes and solutions of target’s location, the reasonable planning and optimal layout of passive transducers’ location are other major factors affecting the precision of localization. Planning an optimal airspace for passive transducers is the key problem to improve the monitoring efficiency. This paper proposes the optimal layout algorithm for the cooperative platform in the space based on the geometrical relationship of cooperative localization. For example, the principle of direction location in traditional methods is simple: only two passive sensors can work, but the location accuracy of long-distance targets is low. At the same time, TDOA (Time Difference Of Arrival) location has high accuracy and good stability, but it needs at least three passive sensors to work together, which requires the most resources. In this paper, a platform optimization layout algorithm based on direction and TDOA hybrid positioning is proposed. Compared with direction positioning, it improves the long-distance positioning accuracy, reduces the number of sensors required for TDOA positioning, and reduces the resource occupancy rate. However, the TDOA positioning data mixed with direction positioning data inevitably leads to the decline of overall accuracy. In order to solve these difficulties, the weighted least square method is used to optimize the accuracy. The simulation shows that, within the designated target airspace, the optimal action airspace can be generated automatically based on the platforms’ cooperation mode. If there is no resource limitation, the airspace planning based on TDOA positioning has the highest accuracy for the target. However, in practical application, considering the resource limitation, the hybrid positioning of direction and TDOA can also meet the requirements of high accuracy and high stability. The average error is reduced by more than 45% compared with direction positioning, and the airspace occupancy is reduced by more than 30% compared with TDOA positioning. The goal of minimizing the scope of platform airspace planning is realized. Full article
(This article belongs to the Special Issue Modelling, Control and Emerging Application for Unmanned Vehicles)
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