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BAE Systems Work MAJICS for DARPA

HALLMARK-TECM Aimed at Better Space Situational Awareness

BAE Systems has been awarded a Phase 2 contract to develop machine learning capabilities aimed at helping the military gain better awareness of space scenarios for the US Defense Advanced Research Projects Agency (DARPA). The goals of DARPA’s HALLMARK Tools, Capabilities and Evaluation Methodology (Hallmark-TCEM) programme are not only to develop and evaluate tools and capabilities that increase an operator’s understanding of space events, but also to enhance the ability to select effective courses of action for any given situation.

Space assets such as satellites are becoming increasingly important and relied upon by the Department of Defense (DoD) for communications, surveillance, and security. As part of HALLMARK-TCEM, BAE Systems’ FAST Labs research and development team will build cognitive-based machine learning algorithms and data models aimed at giving space operators the ability to identify abnormal activities and predict possible threats. The team will build on Phase 1 work of the programme and continue to leverage the decade-long development of the company’s Multi-INT Analytics for Pattern Learning and Exploitation (MAPLE) technology, with a solution called MAPLE Automates Joint Indications and Warnings for Cognitive Counter-Space (MAJICS).

Our technology builds data models based on normal activity and then ingests large amounts of real-time, streaming data to compare against the normal model and determine if any abnormal activity is occurring or will occur,” commented BAE Systems’ Sensor Processing and Exploitation Group’s Product Line Director, Dr John Hogan. “By using this technology, we hope to reduce the operator’s workload by providing a solution that will automatically predict space events such as launches or satellite movements based on millions of pieces of data, helping them make rapid decisions to avoid any potential threats.”

BAE Systems’ research on the HALLMARK-TCEM program adds to the company’s machine learning and artificial intelligence segment of its autonomy technology portfolio. The capabilities developed under the effort will be integrated into DARPA’s HALLMARK Software Testbed (HALLMARK-ST) programme.

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