Machine Learning And RF Spectrum Intelligence Gathering

By Dr. Michael Knott, Research Engineer, CRFS Ltd.

To classify a signal in RF spectrum intelligence gathering, the user must recognize a specific pattern associated with the modulation. Additionally, to recognize a remarkable signal present in received data, the pattern must be distinguished from the noise. The human brain is good at pattern recognition, but it is more desirable to automate these applications for efficiency - and to avoid errors cause by human fatigue. However, since computers are not good at applying predetermined algorithms, machine learning (ML) is better suited to the problem. This white paper discusses using ML to automate pattern recognition processes as part of a suite of EW tools. Download the full paper for more information.