RF Sensor Performance in Electrically Large, Complex Environments

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$149,847.00
Award Year:
2007
Program:
SBIR
Phase:
Phase I
Contract:
N68335-07-C-0212
Agency Tracking Number:
N071-023-0752
Solicitation Year:
2007
Solicitation Topic Code:
N07-023
Solicitation Number:
2007.1
Small Business Information
DELCROSS TECHNOLOGIES, LLC
223 East Sixth Street, PO Box 676, Neoga, IL, 62447
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
782768977
Principal Investigator:
Robert Kipp
Chief Scientist
(312) 431-7413
kipp@delcross.com
Business Contact:
Matthew Miller
President
(217) 895-2067
mcmiller@delcross.com
Research Institution:
n/a
Abstract
Modern military and commercial aircraft include numerous RF systems and associated antennas serving a multitude of functions. Typically, the designed free space performance of antennas is degraded by their installation on the airframe. Also, the presence of many RF systems in a small region creates enormous opportunity for undesired inter-system electromagnetic interference (EMI) via antenna-to-antenna coupling. These facts present the antenna/platform integrator with an enormous problem: how to place the numerous antennas on the airframe so that they can perform their stand-alone functions while minimizing interference. We propose to develop a tool that implements asymptotic ray tracing on electrically-large, high-fidelity airframe CAD models to accurately predict installed antenna performances and co-site interference. Phase I will focus on proof-of-concept development and validation core and advanced methods. In Phase II, the computational engine will be coupled with a sophisticated graphical user interface (GUI), with emphasis on visualization to aid the user in problem setup, multi-system management, and interpretation of results. The tool will offer advantages over existing asymptotic solvers through more accurate near field interactions, creeping wave algorithms for realistic geometries, and powerful diagnostic features.

* information listed above is at the time of submission.

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