SignalEye™: Machine Learning Automation for SIGINT
May 01, 2019Download PDF
Authored by David Ramirez at General Dynamics Mission Systems featuring Curtiss-Wright Defense Solutions
Electromagnetic warfare and wireless communications continue to evolve. An opportunity exists to leverage modern technology to improve military signals intelligence to enable our own forces to be more lethal, agile, and survivable. Massive amounts of wireless data can overwhelm traditional SIGINT methods. Automation through machine learning algorithms speeds detection and classification of signal data. General Dynamics designed SignalEye™ to automate tedious SIGINT tasks, freeing time for complex human decision making. It also accelerates engagements to address vexing short dwell targets. SignalEye integrates into 3rd party software defined receiver platforms, turning any radio into a SIGINT platform. It also processes backlogs of signal data, such as months of data stored on a commodity server. SignalEye ingests radio data, automatically detects and isolates observed signals, and automatically determines the modulation type. SignalEye allows for faster outcomes than manual methods through automation. Confidence measures, reported to the users, back up machine learning results. Our patent pending machine learning framework can specialize to specific Area of Responsibility (AOR) and terrain. This tool revolutionizes the processing of signal data into actionable intelligence.
Operating in the electromagnetic spectrum keeps getting more demanding. In foreign countries, tactical communications might once have been the only signal on the airwaves. Today, the use of wireless technologies has exploded worldwide. The number of mobile devices has surpassed the number of humans on this planet. Civilian cell service, Wi-Fi, satellites, and radio waves penetrate every corner of the globe. The majority of these devices operate on expected frequency bands, but many do not. Especially in developing markets with minimal regulation, the prevalence of interfering transmitters is growing rapidly.
Automation can greatly improve communications planning and SIGINT capabilities. Artificial intelligence augments human capabilities to reduce latencies and improve outcomes. An automated algorithm detects and identifies signals in sensor data much faster than a highly trained operator.