Lock-In Acousto-Optic Correlator

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: N/A
Agency Tracking Number: 28636
Amount: $99,960.00
Phase: Phase I
Program: SBIR
Awards Year: 1995
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
Dynetics, Inc.
P.o. Drawer B, Huntsville, AL, 35814
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Michael Zari
 (205) 922-9230
Business Contact
Phone: () -
Research Institution
N/A
Abstract
Dynetics proposes an innovative combination of analog and digital technology to produce a Lock-In Acousto-Optic correlator for application in pulse-coupled neural networks. Our unique approach uses a time-integrating optical correlator and high-speed, two-dimensional digital processing for matched filtering of repetitious waveforms of unknown pulse repetition frequency (PRF). Dynetics' proposed approach is beneficial for the following reasons: 1) the correlator optimizes signal-to-noise ratio (SNR) regardless of PRF, 2) the correlator is reprogrammable for any waveform type 3) the processor operates in very low SNR environments, and 4) the correlator rapidly locks onto the PRF using a non-iterative algorithm. By combining a neural network image processor and a Lock-In Acousto-Optic Correlator, a new product would be available for many facets of image recognition. A well-recognized commercial market for image recognition processors already exists in the areas of manufacturing and quality control. Dynetics is confident that the Lock-In Acousto-Optic Correlator can be developed using low cost components, making the final product marketable. In this proposal, Dynetics describes a Phase I effort that will provide a convincing demonstration and will lay the groundwork for achieving commercialization in Phases II and III. ANTICAPTED BENEFITS: The development of a combined pulse-coupled neural network and Lock-In Acousto-Optic Correlator would significantly impact both Government and commercial users because of the long established need for image recognition devices. Commercial users would benefit in many facets of machine vision-based manufacturing and quality control systems. Military users would benefit in the areas of vision-based automatic target acquisition and non-cooperative identification of friend-or-foe (IFF) systems.

* information listed above is at the time of submission.

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