Dear Colleagues,

Today, unmanned aerial vehicles (UAVs) have attracted huge interest within academia and industry as well as among practitioners. UAVs find many civil and military applications related to remote sensing, surveillance, law enforcement, target detection and tracking, and improvement of wireless communications. Further, complex tasks can be delegated to swarms of small cooperating UAVs to gain in flexibility, efficiency, coverage, and reliability.  

In all these scenarios, UAVs are expected to jointly optimize accuracy in sensing the environment, in processing the gathered data, in planning their trajectories and in reconfiguring themselves (e.g., their formation or communication links) as a response to some sensed events, possibly through cooperation. To preserve the UAVs’ energy autonomy and relax the mission time, it is also essential to keep the complexity low, whereas the adoption of low-cost on-board technology enables the realization of large networks of cooperating UAVs.

To deal with a complex system of cooperating agents, there is the need to design methods capable of finding a good tradeoff between heterogeneous and sometimes competing requirements and of learning a decision-making policy through sensing interactions with the environment. In this direction, in addition to well-established optimization methods, artificial intelligence (AI) can offer promising solutions. 

This Special Issue seeks papers dealing with UAV networks where environmental awareness through sensing is empowered by intelligent decision-making. We welcome new contributions focusing on technological and algorithmic advancements, practical designs, and experiments as well as new communication strategies for and through UAV networks. Topics of interest include but are not limited to the following:

• Sensing technologies for UAV networks
• Aerial intelligent reflecting surface
• Cellular-connected UAVs towards 6G
• Aerial passive radars
• Multistatic and monostatic UAV radar networks
• Target detection and tracking algorithms
• Sensing and communication co-design for UAV networks
• Sensor fusion for UAV networks
• Control and decision-making in UAV networks
• UAV-to-UAV and UAV-to-Everything communication
• Machine learning for UAV decision making
• Model based optimization
• UAV trajectory estimation and formation control
• Signal processing over dynamic and distributed UAV networks
• Test-bed, trials and experimentations using UAVs

Dr. Anna Guerra
Dr. Francesco Guidi
Prof. Davide Dardari
Prof. Dr. Petar M. Djuric
Guest Editors

Manuscript Submission Information

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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.

• Unmanned aerial vehicles
• Radar
• Target detection and tracking
• Sensor fusion
• UAV Control
• Intelligent decision-making
• Machine learning
• Communication
• Distributed signal processing
• Dynamic flying wireless networks