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Adaptation of the Stuff Algorithm to Realistic Measurement Scenarios

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
97429
Program Year/Program:
2010 / SBIR
Agency Tracking Number:
F093-156-0814
Solicitation Year:
N/A
Solicitation Topic Code:
AF 09-156
Solicitation Number:
N/A
Small Business Information
DECISIVE ANALYTICS Corporation
1235 South Clark Street Suite 400 Arlington, VA -
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2010
Title: Adaptation of the Stuff Algorithm to Realistic Measurement Scenarios
Agency / Branch: DOD / USAF
Contract: FA8650-10-M-1852
Award Amount: $99,999.00
 

Abstract:

Identifying non-cooperative and potentially hostile vehicles is of the utmost importance to the operators of manned and un-manned surveillance aircraft. Utilizing ISAR imagery has been one method for performing target identification by many organizations. However, the complicated motions of the target vehicle and ISAR platform often prevent a clear 2D image from being recovered. Over the course of the previous 10 years, methods have been developed to utilize the complicated target motions to convert 1D range data into a 3D image of the target. The methods, however, have thus far not been able to stand up to application of real data. The presence of scatterers not attached to the rigid target body and scatterers which are not visible for wide view angles both cause difficulties for these methods. The DAC-MTRI team proposes new algorithms and systems which will begin to handle these issues. The approach will create a step forward in creating a continuous link between ISAR measurements, advanced imaging techniques, and target recognition systems. BENEFIT: As the need for automatic target recognition systems increases, the ability to produce reasonable images of target objects increases as well. This work will expand on the methods developed over the previous 10 years which produce 3D images based on 1D ISAR range data. The ability to handle noisy data with non-persistent scatterers is a significant obstacle in the development of these methods. With the systems presented in this work, we plan to overcome many of these difficulties.

Principal Investigator:

Douglas Ratay
Senior Engineer
7036821514
douglas.ratay@dac.us

Business Contact:

Kelly McClelland
VP, Administration
7034145024
kelly.mcclelland@dac.us
Small Business Information at Submission:

DECISIVE ANALYTICS Corporation
1235 South Clark Street Suite 400 Arlington, VA 22202

EIN/Tax ID: 541785147
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No