Affordable Scalable Acoustic Panel Arrays

Award Information
Agency:
Department of Defense
Amount:
$79,984.00
Program:
SBIR
Contract:
N00024-12-P-4063
Solitcitation Year:
2012
Solicitation Number:
2012.1
Branch:
Navy
Award Year:
2012
Phase:
Phase I
Agency Tracking Number:
N121-055-0061
Solicitation Topic Code:
N121-055
Small Business Information
ASSETT, Incorporated
11220 ASSETT Loop, Suite 101, Manassas, VA, -
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
020910951
Principal Investigator
 Bob McCaig
 Senior Vice President
 (703) 365-8940
 bob.mccaig@assett.net
Business Contact
 Galen Plunkett
Title: Sr Vice President, COO
Phone: (703) 365-8970
Email: galen.plunkett@assett.net
Research Institution
 Stub
Abstract
Sonar performance is highly dependent on the performance and positional accuracy of its acoustic sensors. Today"s arrays are populated with sensors built to strict tolerances to minimize channel to channel differences and precision mounted to enable the exact location, speed, direction of motion, and classification of a contact. Knowing the precise location of each sensor and its performance characteristics is key to sonar performance. The lack of precision or performance within a tolerance range can result in vessels being dry docked in order to manually recalibrate the array of sensors. Once the platform is deployed, mechanical stress, hull dynamics, pressure loading variations, element electronics variability, and element failures all tend to degrade performance. Manual replacement, recalibration, and installation of array sensors due to failure or degradation involves significant cost. ASSETT teamed with NGUS provides a total system solution by addressing both the sensor technology and mounting requirements as well as the application of signal processing to allow for a wider tolerance in the sensor performance while maintaining or increasing system performance. The major elements of the technologies proposed by the ASSETT Team have been proven and implemented on other platforms resulting in a low risk effort for this SBIR.

* information listed above is at the time of submission.

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