Raytheon Tests Data Analysis Method for Tactical Ground Station; David Appel Quoted

David Appel VP Raytheon Technologies
David Appel, VP, Raytheon Technologies

Raytheon Technologies’ intelligence and space business has demonstrated an activity-based intelligence methodology for a ground station being developed to help military users receive data and find potential threats on the battlefield.

The company said Monday it tested the analysis approach as part of a demonstration for the U.S. Army's Tactical Intelligence Targeting Access Node system – also known as TITAN.

The forward-deployed terminal is intended to autonomously process huge amounts of data from sensors and work with the Department of Defense's future Joint All Domain Command and Control network.

The ABI methodology seeks to accelerate the multisource data integration process as well as support pattern discovery and change identification tasks.

During the exercise, the RI&S team used ABI to process imaging data from five sensor types and applied a 3D model of Earth using a point cloud technology in addition to extracting data for target identification.

David Appel, vice president of R&I's defense and civil solutions for space and C2 systems, said that predictive algorithms and artificial intelligence combined with 3D cloud concepts helped the team optimize available data sources.

“For us to move faster, we’re going to have to trust the machine-learning automation,” Appel added.

The Army awarded Raytheon and Palantir Technologies separate 12-month, $8.5M other transaction agreements earlier this month mature system design and software for the TITAN program.

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