Dogan,D.Dalveren,Y.Kara,A.Department of Electrical & Electronics EngineeringMechatronics Engineering2024-07-052024-07-0520222978-166549485-410.1109/COMM54429.2022.98171892-s2.0-85135144456https://doi.org/10.1109/COMM54429.2022.9817189https://hdl.handle.net/20.500.14411/4071Forvia; MarcTel; Orange; Orion InnovationA considerable growth in demand for locating the source of emissions in outdoor environments has led to the rapid development of various localization methods. Among these, RF fingerprinting (RFF) localization has become one of the most promising method due to its unique advantages resulted from the recent developments in machine learning techniques. In this short review, it is aimed to assess the existing RFF methods in the literature for outdoor localization. For this purpose, firstly, the current state of RFF localization methods in outdoor environments are overviewed. Then, the main research challenges in the development of RFF localization are highlighted. This is followed by a brief discussion on the open issues in order to give future research directions. Furthermore, the research efforts currently undertaken by the authors are briefly addressed. © 2022 IEEE.eninfo:eu-repo/semantics/closedAccessdeep learningestimationlocalizationmachine learningRF fingerprintingConference Object