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Monterey Technologies, Inc. SBIR Phase II Award, November 2017

A SBIR Phase II contract was awarded to Monterey Technologies, Inc. in November, 2017 for $749,906.0 USD from the U.S. Department of Defense and United States Navy.

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Contents

sbir.gov/node/1474041
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Monterey Technologies, Inc.
Monterey Technologies, Inc.
0
Government Agency
U.S. Department of Defense
U.S. Department of Defense
0
Government Branch
United States Navy
United States Navy
0
Award Type
SBIR0
Contract Number (US Government)
N68335-18-C-00160
Award Phase
Phase II0
Award Amount (USD)
749,9060
Date Awarded
November 7, 2017
0
End Date
July 23, 2019
0
Abstract

The proposed Phase II.5 ViPER USMC large mission planning mission planning expansion effort seeks to add capabilities to ViPER-CVW that will provide an initial large force air planning capability to USMC aviation planners. Development will focus on providing route and airspace deconfliction tools which link airspace, flight routing, and planned aircraft movements, as well as automated checks to ensure route and airspaces do not overlap. Additionally, MTI will provide USMC planners the ability to dynamically share planning constraints and mission requirements with the broader MAGTF team. ViPER CVW has added a collaborative planning capability that allows multiple dispersed ViPER users to share a common planning picture amongst dispersed users, which will be extended into the USMC planning arena. Products applicable to the broader MAGTF team will also be provided with platform specific planning data and force-level planning information that integrate with KILSWITCH electronic kneeboard card tablet and other tools. While not providing a total solution for sharing planning data and application services throughout the USMC battlespace, ViPER does provide a compelling environment in which to capture multi-aircraft and multi-mission planning decisions which can then be evaluated for feasibility, effectiveness, and other constraints by advanced decision aids.

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