Airborne ASW System Interferer Minimizer

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0131
Agency Tracking Number: N182-116-0605
Amount: $124,945.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N182-116
Solicitation Number: 2018.2
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-10-19
Award End Date (Contract End Date): 2019-04-15
Small Business Information
310 5th St., Charleroi, PA, 15022
DUNS: 187594788
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jenting hsu
 (724) 483-3946
Business Contact
 Eli Polovina
Phone: (724) 483-3946
Research Institution
To reduce the false positive and false negative detection and identification of submarines, Nokomis proposes to build an artificial intelligence (AI) algorithm suite, in conjunction with its ultra-sensitive signal detection capability, to minimize the in-band interferences on existing airborne anti-submarine warfare (ASW) systems.
To minimize the background noise and interference, the signal sources in underwater acoustic signals will be isolated. In addition to this, in some environmental conditions a submarine could hide between layers of different temperatures or different salt concentrations that greatly influence the sound propagation and make the target even harder to detect. In a shallow-water archipelago, these problems are further compounded by strong reverberation effects, caused by sound reflection from the sea floor, the surface, and islands, which lead to subsequent interference phenomena.
The proposed technique includes three major steps. The first step is to remove the random noise by wavelet based denoising processing. The second step is to enhance the contrast of signal source of interest from acoustic signal. The third step is to isolate the signal sources of interest from acquired acoustic signal. The third step involves feature extraction processing, waveform matching processing, and AI based deep learning processing.

* Information listed above is at the time of submission. *

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