Journal
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
Volume 55, Issue 5, Pages 2516-2531Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAES.2019.2891155
Keywords
RF signals; Deep learning; Modulation; Feature extraction; Training; Hardware; Field programmable gate arrays; Automated modulation classification (AMC); deep learning; low-complexity deep belief network; microunmanned aerial system (UAS); radio signals classification
Ask authors/readers for more resources
This paper proposes a deep learning based intelligent method for detecting and identifying radio signals considering two applications: first, cognitive radar for identifying micro unmanned aerial systems and second, an automated modulation classification scheme for cognitive radio, which can be used for aeronautical communication systems. Our proposed intelligent method is designed of a spectral correlation function based feature extractor and a low-complexity deep belief network classifier with low FPGA logic utilization.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available