Submarine Sensor Environmental Inference ---- 18-075

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-18-C-0807
Agency Tracking Number: N182-135-0377
Amount: $124,884.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N182-135
Solicitation Number: 2018.2
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-10-15
Award End Date (Contract End Date): 2019-04-18
Small Business Information
1818 Library Street, Reston, VA, 20190
DUNS: 107939233
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 John Gebbie
 (703) 467-5631
 gebbie@metsci.com
Business Contact
 Seth Blackwell
Phone: (703) 326-2907
Email: blackwell@metsci.com
Research Institution
N/A
Abstract
A new optimal sequential Bayesian algorithm is proposed that processes ambient ocean noise collected on the submarines passive sonar sensors into estimates of key aspects of the water sound speed profile (SSP), sea state (SS), and bottom loss (BL). Two modes of operation are proposed. In tracking mode, the software tracks changes in the environmental parameters and sends real-time updates to the submarine tactical decision aid (STDA). In analysis mode it reprocesses previously recorded element-level data stored on the BQH-9 to produce a through-the-sensor environmental hindcast. This provides an enhanced forward-deployed reconstruction capability. Architecturally, the software will run on the compute engine inside the BQH-9. The proposed inferencing capability is made possible by pivoting from the traditional beamforming-based environmental inversion methodology to an information theory based methodology. In Phase I, we intend to use the Cramr-Rao lower bounds and unclassified data to gain insight into which parameters can be estimated by the different submarine sensors. This will lend insight into the design of the environmental tracker.

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

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