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Inverse Synthetic Aperture Radar (ISAR) Imagery Feature Extraction and Database

Award Information

Agency:
Department of Defense
Branch:
Navy
Award ID:
82588
Program Year/Program:
2007 / SBIR
Agency Tracking Number:
N071-044-0550
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Cybernet Systems Corporation
3885 Research Park Drive Ann Arbor, MI 48108-2247
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Woman-Owned: Yes
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2007
Title: Inverse Synthetic Aperture Radar (ISAR) Imagery Feature Extraction and Database
Agency / Branch: DOD / NAVY
Contract: N68335-07-C-0346
Award Amount: $79,979.00
 

Abstract:

The U.S. military uses a wide range of sensing modalities for collecting data with which to perform automatic target recognition (ATR) and classification. ATR is a crucial capability for today's weapons systems and is used for guiding smart munitions as well as tracking assets or entities of interest. The available sensor modalities include Synthetic Aperture Radar (SAR), Inverse SAR (ISAR), High Resolution Radar (HRR), and Electro-Optical/Infrared (EO/IR), among others. While significant ATR packages have been researched and developed for the individual sensor modalities, no significant effort has been undertaken to create a single ATR method to extract information from all of these disparate data sources. Cybernet proposes to leverage an orientation invariant ATR technique that we developed for EO/IR data for the Navy to develop a new ATR system for use with all data types. This technique combines the power of modern computer graphics with standard ATR concepts to create a very flexible recognition and classification system.

Principal Investigator:

Glenn Beach
Research Engineer
7346682567
gbeach@cybernet.com

Business Contact:

Charles J. Cohen
VP Research and Development
7346682567
proposals@cybernet.com
Small Business Information at Submission:

CYBERNET SYSTEMS CORP.
727 Airport Boulevard Ann Arbor, MI 48108

EIN/Tax ID: 430924383
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No