SBIR/STTR Research Award

COMPUTERIZED SCHEDULED GRADUAL REDUCTION FOR SMOKING

Award identifier 77e11bc4a1dd7fa20a93e761cec68ce46bb3fb2c76b70e41221f095d1b3400f4Awarding agency Department of Health and Human Services

Award amount

$99,836

Program and phase

SBIR · Phase I

Award year

1999

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Award details

Awarding agency
Department of Health and Human Services
Branch
Not reported
Recipient company
PERSONAL IMPROVEMENT COMPUTER SYSTEMS
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
Not reported
Topic code
Not reported

Research abstract

Not Available A set of advanced broadband processing algorithms and a broadband classifier are being proposed for clutter rejection and detection/classification of weak targets in sonobuoy returns. Novel algorithms for the harsh shallow water acoustic environment are needed since the threat model for the ASW has shifted from deep to shallow water. Recent efforts by the underwater community have identified the advantages of using broadband signals and new processing techniques to limit the effects of reverberation. This effort proposes an unconventional approach that exploits the broadband nature of explosive or impulse-like sources, as well as the new generation of coherent broadband acoustic sources the Navy uses. This broadband approach achieves very good array gain and dynamic range using a limited number of sensors. This technique uses degrees of freedom in the frequency domain, by drawing an analogy with degrees of freedom in space in a discrete line-array. The algorithms being proposed include broadband adaptive filtering, beam canceling and modified eigen-vector beamforming techniques. These algorithms are used to feed a broadband classifier based on a time/frequency wavelet analysis, and are expected to enhance the performance of future ASW systems operating in high clutter environments.

Technology keywords

Not reported

Agency intelligence

Department of Health and Human Services

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