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Development of Explosive Non-Acoustic Sensing on Remotely Operated Vehicles for Littoral Threat Characterization in Complex Seabed Environments

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0049
Agency Tracking Number: N17A-015-0082
Amount: $498,126.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: N17A-T015
Solicitation Number: 17.A
Solicitation Year: 2017
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-11-07
Award End Date (Contract End Date): 2019-11-06
Small Business Information
1242 Chestnut Street
Newton, MA 02464
United States
DUNS: 078673633
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Greg Schultz
 Chief Technologies
 (603) 678-8385
Business Contact
 Edmund Reiter
Phone: (617) 851-6152
Research Institution
 Woods Hole Oceanographic Institution
 David A. Stephens David A. Stephens
266 Woods Hole Road
Woods Hole, MA 02543
United States

 (508) 289-3542
 Nonprofit College or University

White River Technologies, Inc. proposes this effort involving non-acoustic sensing methods and sensor fusion technologies to detect and characterize seabed objects of interest in littoral environments relevant to US Naval activities. Current and evolving threats to maritime dominance require the Navy to adapt to potential hazards from a variety of sources, which could include terrorism, and to operate in increasingly difficult environments. Objects of interest may be hidden or obscured by seabed features such as vegetation, corals, rocks, biologics, man-made debris, and scouring/burial. Our concept will provide an improved capability to localize and classify objects of interest in complex seabed conditions that currently pose a challenge to successful identification of objects using traditional methods. Our concept is based on multi-axis/multi-sensor methods deployed from unmanned systems such as small inspection-class remotely or autonomously operated vehicles to provide advanced classification and target identification capabilities that fill these gaps. Our multi-sensor approach will significantly improve target classification, identification and localization, and provide effective clutter rejection capability. The projected capability is focused on near-term (1-2 years) demonstrations of a TRL-6 system tightly integrated with Naval unmanned assets.

* Information listed above is at the time of submission. *

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