Detection and classification architecture for sdr based radar electronic support measure systems

Abstract

Electronic Support Measures (ESM) devices are key to situational awareness of the electromagnetic environment in the field. However, the current ESM systems tend to be physically large and cumbersome. To mitigate this problem, a portable ESM device is proposed. In this work, a compact single-board computer (SBC) is coupled with a Software Defined Radio (SDR) to create such a device. Signals received by the SDR are sampled within the SDR and sent to the SBC. Those signals are then processed with various signal processing and machine learning algorithms to perform detection, measurement, and classification tasks. Later, these results are reported to the user.