Adaptive Beamforming for Littoral Waters

Award Information
Agency:
Department of Defense
Amount:
$66,650.00
Program:
SBIR
Contract:
N/A
Solitcitation Year:
N/A
Solicitation Number:
N/A
Branch:
Navy
Award Year:
1996
Phase:
Phase I
Agency Tracking Number:
32577
Solicitation Topic Code:
N/A
Small Business Information
Digital System Resources, Inc.
12450 Fair Lakes Circle, Fairfax, VA, 22033
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
N/A
Principal Investigator
 Stuart F. Adams
 (703) 263-2800
Business Contact
Phone: () -
Research Institution
N/A
Abstract
This project proposes preliminary investigations to prove the feasibility of four techniques for improving Adaptive Beamforming performance in littoral environments. Emphasis is placed on tradeoffs between algorithm efficiency and performance. The littoral acoustic environment is characterized by near and far field targets and dense dynamic near and far field directional interference at many ranges and levels of stationarity. Unique applications of Sub-Aperture Spatial Processing and Parabolic Near Field Wave Front Approximation techniques are proposed as efficient techniques to reduce target suppression caused by a mismatch between the Adaptive Beamforming constraints and the near field acoustic wave front and sensor array shape estimates. A third technique uses Synthetic (array data) Covariance Estimates made from conventional beam spatial spectra for adaptive beamforming weights computation to provide a fast low throughput weight updating technique in dynamic signal fields. The fourth technique provides an innovative approach for passive target range estimation by using Near Field Adaptive Beamforming Focused Range Zones. Theoretic performance calculations will be made based on spatial covariance data models that will incorporate wave front and array shape uncertainties and dynamic source geometries. When possible limited amounts of real data will be used. Signal processing gains and processing resource requirements will be tabulated with the most promising techniques selected for an extensive real data evaluation in Phase 2.

* information listed above is at the time of submission.

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