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Mercury Computer Systems announces $2.7 million order for Predator upgrade

13th July 2009 - 21:00 GMT | by The Shephard News Team

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Mercury Computer Systems has announced it has received a $2.7 million production order from General Atomics Aeronautical Systems to provide RACE++ Series rugged computing modules for the Predator unmanned aircraft system (UAS) Lynx Block 20 synthetic aperture radar (SAR) technology upgrade.

Since 1998, Mercury has continued to provide its scalable RACE Series and RACE++ Series computing modules and software to enable high-performance signal processing for multiple generations of GA-ASI's Lynx SAR product line.

The Lynx family of SAR reconnaissance and surveillance systems, along with Mercury's signal processing modules, are installed on a variety of Predator series UAS. As the most combat-proven unmanned aircraft system in the world, the Predator UAS provides continuous and persistent armed reconnaissance and battlefield support to ground troops.

The Lynx Block 20 radar upgrade is an extension of a production run requested by the U.S. Air Force and will bring the number of signal processing computing modules that Mercury has provided to GA-ASI to more than one thousand.

"GA-ASI's world-class family of Lynx SAR systems and Predator UAS continues to be deployed extensively on reconnaissance and surveillance missions, bringing all-weather, very-high-resolution imagery to the warfighter. The picture-quality imagery provided by the Lynx radar would not be possible without Mercury's reliable, scalable, high-performance computing modules and interconnect technology," said Brian Hoerl, Vice President of Worldwide Sales for Advanced Computing Solutions at Mercury.

"Our processor upgrades enable the Lynx radar to continue to give the warfighter leading-edge performance within the current size, weight, and power constraints of the UAS. This is yet another demonstration of how our technology road map has enabled customers to seamlessly upgrade their system performance and accelerate their embedded computing applications."

 

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