LFA and CFLA Acoustic Sensors

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00024-13-P-4018
Agency Tracking Number: N131-050-0466
Amount: $79,941.00
Phase: Phase I
Program: SBIR
Awards Year: 2013
Solicitation Year: 2013
Solicitation Topic Code: N131-050
Solicitation Number: 2013.1
Small Business Information
Adaptive Methods, Inc
5860 Trinity Parkway, Suite 200, Centreville, VA, -
DUNS: 135121148
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Walt Allensworth
 Principal Investigator
 (301) 840-9722
 wallensworth@adaptivemethods.com
Business Contact
 Judy Barhorst
Title: Director of Contracts
Phone: (703) 968-6110
Email: jbarhorst@adaptivemethods.com
Research Institution
 Stub
Abstract
Challenges faced today by the U.S. Navy"s ASW forces are due to the increasing number of diesel-electric submarines operated by some nations. These threats faced by the U.S. Navy have become increasingly difficult to locate using traditional passive acoustic sonar due to the advancement of quieting technologies in submarines. Low-Frequency Active (LFA) and Compact Low-Frequency Active (CLFA) sonars were developed to improve the detection range of these quiet submarines. LFA and CLFA were originally designed for use in a deep-water, low-clutter environment. Active clutter has significantly increased as these active sonars moved from deeper water to littoral environments. Adaptive Methods proposes to develop an active adaptive beamformer (ABF) for LFA and CLFA which provides improved active clutter reduction and improved signal to interferer and noise ratio. ABF algorithms ability to suppress loud acoustic interference arriving in the sidelobe region of beams will reduce clutter and improve detection performance. Adaptive Methods proposes to apply our approach to Robust Adaptive Matched Filtering to beamformed data that will improve the detection of weak signals of interest normally masked by loud interference in correlations. The feasibility of our concepts will be demonstrated by use of simulated data and comparison to the existing processing system.

* information listed above is at the time of submission.

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