SBIR/STTR Research Award

Lock-In Acousto-Optic Correlator

Award identifier 11d4430a5eae3a9f1a4615e7f4c8eb2f3489bfbbe6e658bae8d8b800f8eea8deAwarding agency Department of Defense · Defense Advanced Research Projects Agency

Award amount

$99,960

Program and phase

SBIR · Phase I

Award year

1995

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Award details

Awarding agency
Department of Defense
Branch
Defense Advanced Research Projects Agency
Recipient company
DYNETICS, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
Not reported
Topic code
Not reported

Research 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.

Technology keywords

Not reported

Agency intelligence

Department of Defense

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