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KVHI KVH Industries Inc

4.49
-0.05 (-1.10%)
Last Updated: 20:07:29
Delayed by 15 minutes
Share Name Share Symbol Market Type
KVH Industries Inc NASDAQ:KVHI NASDAQ Common Stock
  Price Change % Change Share Price Bid Price Offer Price High Price Low Price Open Price Shares Traded Last Trade
  -0.05 -1.10% 4.49 4.49 4.51 4.66 4.42 4.58 33,850 20:07:29

New KVH Series 1750 IMU Offers Breakthrough Performance in Ultra Compact Form Factor

06/06/2012 5:30am

GlobeNewswire Inc.


KVH Industries (NASDAQ:KVHI)
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KVH Industries, Inc., (Nasdaq:KVHI) introduces the new Series 1750 Inertial Measurement Unit (IMU), an advanced 6-degrees-of-freedom sensor (DOF) designed to integrate easily into the most demanding stabilization, pointing, and navigation applications, enhancing performance at a lower cost than competing systems. The Series 1750 IMU marries the groundbreaking E•Core® ThinFiber™ technology of KVH's DSP-1750 fiber optic gyro (FOG) with very low noise, solid state MEMS accelerometers to create a commercial-off-the-shelf IMU. The Series 1750 IMU offers exceptional precision in a very small form factor, making it ideal for applications where space is limited, such as unmanned and autonomous systems.

"System designers and integrators have been requesting a convenient, compact solution for applications ranging from stabilization and pointing of high-speed gimbals, cameras, and lasers to autonomous vehicle control and navigation," explains Jay Napoli, KVH's vice president of FOG/OEM sales. "We've developed an IMU that is less costly and offers better performance than competing systems, while also offering an industry standard RS-422 interface along with user programmable data outputs, making it very easy to integrate into new or existing applications. The Series 1750 IMU is the new flagship in a planned series of small, advanced navigation and stabilization system sensor products based on the DSP-1750 FOG and KVH's ThinFiber technology."

KVH's new Series 1750 IMU provides highly accurate 6DOF angular rate and acceleration data. It delivers excellent bias stability (

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