South Australian-based company DEWC Systems and the University of Adelaide’s Australian Institute for Machine Learning (AIML) are teaming up to explore the benefits of artificial intelligence and machine learning in detecting radio frequency signals to support Defence needs.

The collaborative research project builds on the work already undertaken by DEWC Systems and AIML for Phase 1 of the Miniaturised Orbital Electronic Sensor System (MOESS) project – a space-based tactical EW sensor system that provides situational awareness.

DEWC Systems’ chief technology officer Dr Paul Gardner-Stephen, who is spearheading the project, said the collaboration will create a framework for AI-enabled spectrum monitoring and automatic signal classification.

“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,” he said.

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

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