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Darpa’s Simple Plan to Track Targets Everywhere | War On You: Breaking Alternative News

Darpa’s Simple Plan to Track Targets Everywhere

Source: Danger Room

darpa-networked-operations

Most confusing briefing ever? Not just. It’s also a sketch of Pentagon far-out research arm Darpa’s plan to track down and tag “elusive targets” — adversaries who can move, hide and blend in with cluttered environments. And that means more than just next-generation sensors that can penetrate foliage or peer inside “urban canyons.” It means stitching together information collected by different sensors to track a moving object.

Darpa’s 2009 strategic plan offers a fascinating overview of  the different approaches the agency is taking to better track and identify these elusive targets. Some of these, like the Forester foliage- penetrating radar, tackle a specific problem: detecting enemy troops moving under the cover of dense jungle canopy. But another program, called NetTrack, would provide more persistent reconnaissance by linking together and comparing information from different sensors to track a target, even if it moves behind a solid obstruction.

The NetTrack overview on the Darpa website gives few details, but the strategic plan gives a better idea of how it might work. Using software tools, the system could stitch together information from a variety of sensors (synthetic aperture radar, optical, video, acoustic sensors, moving target indicators), and hand off to the right platform when appropriate. For instance, if a Predator lost a video feed on a vehicle that entered a forest, the networked system would cue a laser radar sensor to search for the target. Fusing or comparing sensor information can also help map out better routes for surveillance aircraft to ensure full-time coverage.

Airborne intelligence, surveillance and reconnaissance is a big focus of current operations; the Air Force, for instance, is speeding the deployment of the MC-12W aircraft — a converted Beechcraft King Air twin turboprop that captures full-motion video and signals intelligence. But finding ways to combine sensor information in more sophisticated ways would be the next step toward getting the hooks in a target — and not letting go.

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