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Enabling Netted Sensor Fusion for Anti-Submarine Warfare in Uncertain and Variable Environments

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00167-11-P-0025
Agency Tracking Number: N102-145-0800
Amount: $80,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N102-145
Solicitation Number: 2010.2
Timeline
Solicitation Year: 2010
Award Year: 2011
Award Start Date (Proposal Award Date): 2010-10-18
Award End Date (Contract End Date): N/A
Small Business Information
40 Lloyd Avenue Suite 200
Malvern, PA -
United States
DUNS: 075485425
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Richard Samms
 Associate/President
 (757) 727-7700
 richard@va.wagner.com
Business Contact
 W. Monach
Title: Vice President
Phone: (757) 727-7700
Email: GovtMktg@pa.wagner.com
Research Institution
 Stub
Abstract

Daniel H. Wagner Associates proposes to develop a tool set for object location and classification, and sensor data geo-registration for full distributed platform data fusion and multi-attribute ASW scene generation. The process of accurately locating and identifying tracks and objects using multiple sensors requires that the individual sensor data be properly geo-registered prior to the data fusion, classification, and location refinement processes to avoid false classifications and misidentified threats. Proposed is an innovative method to register multiple sensor data into a high probability scene using a stochastic multi-hypothesis pairwise registration algorithm. The registered data is then post processed using a multi-hypothesis tracker to produce the most likely scenarios. Our approach to advanced geo-registration algorithms to fuse data from multiple platform sensors includes individual sensor performance, multiple attribute, and maximum likelihood optimal assignment. Once a common ASW scene is created we will classify the track with an inferential reasoning engine used to estimate target ID is based on a context dependent Bayesian Network.

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

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