DEWC uses AI to detect RF signals

Electronic Warfare and surveillance technology company DEWC Systems has partnered with the Australian Institute for Machine Learning (AIML) to explore AI and machine learning to detect radio frequency (RF) signals.

AIML, part if the University of Adelaide, and DEWC will detect and classify RF signals in complex environments as part of their Miniaturised Orbital Electronic Sensor System (MOESS) project.

DEWC CTO Dr Paul Gardner-Stephen said that the collaboration would create a framework for AI-enabled spectrum monitoring and automatic signal classification.

Gardner-Stephen said: “Radio spectrum is very congested, with a wide range of signals and interference sources, which can make it very difficult to identify and correctly classify the signals present.

“This is why we are turning to AI and ML, to bring the necessary algorithmic power necessary to solve this problem.

“This will enable the creation of applications that work on DEWC’s MOESS and the Wombat Smart Sensor Suite (Wombat S3) platforms to identify unexpected signals from among the forest of wireless communications, to help defence identify and respond to threats as they emerge.”

The project will include testing the Wombat S3, a ground-based version of the MOESS – both are highly capable software defined radio (SDR) platforms.

DEWC Systems CEO Ian Spencer said the collaborative project would continue to develop sovereign capability in the application of AI and machine learning and provide novel techniques that can support defence needs.

Picture: AIML

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