Development of Cognitive EW Datasets

In this webinar, we will review the challenges that mode-agile radar and EW threat emitters pose to traditional static threat library implementations in radar and EW systems, and assess the architecture of cognitive Artificial Intelligence (AI) and Machine Learning (ML) systems that can be used to deliver effective RF countermeasures. We will then discuss to show how MATLAB can be used to create training datasets for radars, communication systems, and other RF emitters to ensure robust training of deep learning and machine learning algorithms for use in cognitive radio applications. We will demonstrate data synthesis techniques that include the effects of propagation channels, hardware impairments, and interference sources. We will conclude with a discussion of a wideband RF record, simulation and playback system that can be used to create realistic training environments with over-the-air (OTA) measurements of those AI & ML systems running on real-world hardware.

Speaker and Presenter Information

Tim Fountain the Global Market Segment Manager at Rohde & Schwarz, where he is responsible for the RADAR & Electronic Warfare segment. Tim has over 30 years of experience with market leaders in the Test & Measurement industry, focusing on RF and microwave applications in Aerospace & Defense. He started his professional life as an applications engineer and has also held roles in R&D, corporate management, product planning, product marketing and business development. Tim holds a Masters Degree in Electrical and Electronic engineering from University of Hertfordshire in the UK. He is also certified as a chartered professional engineer in Europe. In his spare time Tim likes to fly, and is an instrument rated private pilot.

Michael Rudolph has been the Aerospace and Defense Industry Manager at MathWorks since 2019. In his role, he works with engineering leadership throughout the industry to understand ongoing and emerging technology trends from autonomous systems to multifunction RF systems. Prior to joining MathWorks, he spent a decade at Raytheon BBN Technologies performing interdisciplinary research on various sensor and RF systems for DoD customers like Defense Advanced Research Projects Agency (DARPA). He holds bachelors and master's degrees in engineering from Penn State University, and an MBA from University of Virginia's Darden School of Business.