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Graphics Processing Unit (GPU) Acceleration for Cosite Interference Prediction Tools

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-13-C-0249
Agency Tracking Number: N131-008-0032
Amount: $80,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N131-008
Solicitation Number: 2013.1
Timeline
Solicitation Year: 2013
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-05-15
Award End Date (Contract End Date): 2013-11-15
Small Business Information
3015 Village Office Place
Champaign, IL -
United States
DUNS: 782768977
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Tod Courtney
 Senior Software Engineer
 (217) 363-3396
 tcourtney@delcross.com
Business Contact
 Matthew Miller
Title: President
Phone: (217) 363-3396
Email: mcmiller@delcross.com
Research Institution
N/A
Abstract

Modern military systems contain numerous avionics and electronic systems that must perform to very high standards in hostile environments in the presence of numerous potential sources of electromagnetic interference (EMI). On airborne platforms for example, there could be dozens of RF systems radiating and receiving mission critical signals simultaneously over a very wide range of frequencies. Undesired electromagnetic coupling between these systems can easily occur, leading to loss of function of one or more critical systems. In addition to this cosite interference, there is also the potential for EMI due to sources of electromagnetic energy not located on the platform of interest. These sources of external interference could be due to systems operating on nearby platforms such as a high power radar on a ship, or could be due to intentional jamming. In order to ensure maximum likelihood of mission success, modern military platforms must consider the mitigation of cosite and inter-system EMI prior to deployment, whenever subsystems are added or changed, and periodically during the service life of the platform to ensure continued compliance as the equipment ages. Through this proposed effort, we will show how the GPU-based parallelization of EMIT will lead to significant reductions in simulation time, greatly improve the usability of the tool, and make it possible to add higher-fidelity modeling formulations without sacrificing run time or decreasing the efficiency of the cosite engineers.

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

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