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A Systematic Approach to Uncertainty Analysis for Physical Optics Based Radar…

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
73150
Program Year/Program:
2005 / SBIR
Agency Tracking Number:
F051-212-1551
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
ANALYTIC DESIGNS, INC.
245 East Gay Street Columbus, OH 43215
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2005
Title: A Systematic Approach to Uncertainty Analysis for Physical Optics Based Radar Cross Section Prediction.
Agency / Branch: DOD / USAF
Contract: FA8650-05-M-1864
Award Amount: $99,995.00
 

Abstract:

The model validation process in radar cross section (RCS) database production is time consuming and labor intensive. Typically, synthetically generated data is compared to measured data, which is considered to be "truth." However, one must acknowledge that time may be waisted trying to refine a target model beyond the fidelity capable of the synthetic tools or the measurement data source. Analytic Designs, Inc. proposes to develop a systematic approach to uncertainty analysis for RCS prediction. The measurement community has expended a great deal of time and energy addressing the uncertainty problem in RCS measurements; to our knowledge, no one has attempted a similar systematic analysis of the RCS prediction process. The goal is to develop a mathematical/statistical framework for uncertainty analysis based on Physical Optics (PO) theory for the Perfectly Electrically Conducting (PEC) facetized target. The overall purpose of this Phase I program is to provide tools and outline procedures to improve the efficiency of the synthetic RCS database development process.

Principal Investigator:

Sean W. Gilmore
Principal Scientist
6142249078
swg@adinc.com

Business Contact:

Harry T. Shamansky
President
6142249078
hts@adinc.com
Small Business Information at Submission:

ANALYTIC DESIGNS, INC.
245 East Gay Street Columbus, OH 43215

EIN/Tax ID: 311273608
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No