Fiscal Year	2021
Division	Research & Sponsored Programs
Department	NPS Naval Research Program
Investigator(s)	Kragh, Frank E.
Sponsor	Office of the Chief of Naval Operations (Navy)
Summary	Research has shown that machine learning holds promise as a technique to improve the identification and classification of signals of interest. This study proposes the use of machine learning and generative adversarial networks (GANs) to classify received signals based on their down-converted (but not demodulated) in-phase and quadrature (I&Q) samples and evaluate their probability of being of interest. The approach will use a generative adversarial network (GAN) to train a discriminator neural network that will determine the likelihood that a received signal is of interest. The discriminator can then be used to identify signals of interest as they are received.
Keywords	Neural networks SIGINT generative adversarial networks radio communications
Publications	Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data	Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal