@article{, author = {Khelifi, Manel}, title = {Localization in Unprecedentedly Crowded Airspace for UAVs and SUAVs}, journal = {IEEE Access}, series = {Electronic ISSN: 2169-3536}, volume = {Volume:10}, number = {NSPEC Accession Number: 21818470}, pages = {65206 - 65220}, year = {2022}, month = jun, abstract = {The unprecedented proliferation of Unmanned Aerial Vehicles (UAVs), and Swarm Unmanned Aerial Vehicles (SUAVs) have garnered considerable attention from industry and academia owing to their extensive landscape of applications from disaster relief towards smart agriculture. However, flying several UAVs at once poses many challenges to safely and efficiently localizing and monitoring them. Further, they need to maintain their formation distance to avoid collision between team members and any environmental obstacles. Besides, SUAVs are mainly equipped with an on-board Global Positioning System (GPS) receivers to obtain their positions, but they are not accurate enough and suffer from several vulnerabilities that restrict their applications. Thus, in GPS-denied situations, the acquisition of the positions of UAVs can be assisted by alternative technologies and solutions. This paper is one of the foremost in-depth works that present the topic of localization of SUAVs from various perspectives including current research challenges on positioning systems, telecommunication, and path planning, along with future opportunities on automated delivery services such as medicine, remote inspection of industrial sites, and precision agriculture.}, issn = {2169-3536}, doi = {10.1109/ACCESS.2022.3181377}, url = {https://ieeexplore.ieee.org/document/9791239}, }