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Radar Signature Prediction Code

Award Information

Department of Defense
Award ID:
Program Year/Program:
2003 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
Applied EM Inc.
100 Exploration Way, Suite 300 Hampton, VA -
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 2
Fiscal Year: 2003
Title: Radar Signature Prediction Code
Agency / Branch: DOD / ARMY
Contract: DAAD17-03-C-0068
Award Amount: $729,728.00


Radar signature prediction has been the focus of much research and development for the past 50 years. With the increasing CPU speeds, the focus over the past 15 years has been to develop fast and rigorous simulation tools for composite structures. Evenwith modern computational resources, requirements for modeling large structures overwhelm existing supercomputers. The level of detail in target modeling must be significantly increased since features on the order of a few wavelengths are important for lowRCS calculations. While CEM tools have matured tremendously over the last decade, accurate RCS prediction of realistic ground vehicles at X, Ka and W-bands remains a challenge. Apart from the excessive CPU requirements, there is a need for a practicalintegration of established and modern computational methods to efficiently model materials, composites, and large-scale metallic structures. During Phase I, we proposed a hybrid methodology which forms the basis for a successful integration of theestablished (high frequency and integral methods) and state-of-the-art modern simulation methods along with fast algorithms under a single framework powered through a graphical interface with pre- and post-processing capabilities. Reduced order models forfrequency and angle extrapolations will be also incorporated for generating practical ISAR images.Developed computational tools will be applicable to both radar signature calculations and also for antenna performance predictions. These tools can also beused in the commercial aviation, transportation and security industry. Growing applications also exist in the areas of medical monitoring and imaging.

Principal Investigator:

C.j. Reddy
Presdient & CTO

Business Contact:

President & CTO
Small Business Information at Submission:

24 Research Drive Hampton, VA 23666

EIN/Tax ID: 382962539
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No