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Automatic Target Recognition (ATR) in Complex Underwater Environments

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-23-C-0647
Agency Tracking Number: N231-035-1009
Amount: $139,875.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N231-035
Solicitation Number: 23.1
Timeline
Solicitation Year: 2023
Award Year: 2023
Award Start Date (Proposal Award Date): 2023-08-07
Award End Date (Contract End Date): 2024-02-05
Small Business Information
162 Genesee Street
Utica, NY 13502-1111
United States
DUNS: 111305843
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jonathan Soli
 (315) 765-8703
 soli@brsc.com
Business Contact
 Milissa M. Benincasa
Phone: (315) 732-7385
Email: benincasa@brsc.com
Research Institution
N/A
Abstract

Black River Systems Company, Inc. proposes a novel online machine learning (OML) solution for underwater ATR using acoustic, magnetic, and EO sensors. The proposed solution, called TRACE (Target Recognition Aided by Continuous Evolution), will utilize tailored feature extractors and a robust online Bayesian classifier to maximize ATR performance in challenging underwater environments. TRACE is designed to minimize data overhead and to remain robust in situations when sensor streams are degraded or unavailable. Variational Bayesian ML techniques, the key driver of TRACE, will provide a flexible, and explainable framework for OML. Online updates will be achieved using compact representations of historic samples stored on disk to minimize data overhead and eliminate the need for persistent acoustic comms (ACOMMS). TRACE is easily extended to learn from a fleet of AUVs by populating the database with samples from various assets in real-time or post-mission.

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

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