Cross-Platform SAR Image Quality Metric for ATR

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-10-M-1826
Agency Tracking Number: F093-143-1453
Amount: $99,999.00
Phase: Phase I
Program: SBIR
Awards Year: 2010
Solicitation Year: 2009
Solicitation Topic Code: AF093-143
Solicitation Number: 2009.3
Small Business Information
500 West Cummings Park - Ste 3000, Woburn, MA, 01801
DUNS: 859244204
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: Y
Principal Investigator
 Carl Frost
 Principal Research Engineer
 (781) 933-5355
Business Contact
 Jay Miselis
Title: Corporate Controller
Phone: (781) 933-5355
Research Institution
The intelligence community uses the National Imagery Interpretability Rating Scale (NIIRS) to quantify the information that an image analyst can extract from a visible image; NIIRS ratings are numbers relating quality of an image to interpretation tasks for which it may be used. The General Image Quality Equation (GIQE) is used to predict NIIRS ratings for visible images from parameters such as image resolution, sharpness, and signal-to-noise ratio. There is considerable interest in developing NIIRS image ratings for synthetic aperture radar (SAR) imagery. A new NIIRS prediction equation (SAR GIQE) would take into account both the amplitude and phase of the SAR data, and would be applicable to advanced SAR modes utilized by image analysts in exploitation of SAR data. This new SAR GIQE would represent multiple SAR products generated from complex, full polarization, and/or multi-pass imagery; advanced modes utilizing these data types include detection and recognition, coherent/non-coherent change detection, interferometric and bistatic imaging, super-resolution and ATR processing. SSCI proposes to develop a new SAR GIQE that predicts NIIRS ratings for SAR imagery. BENEFIT: he development of a NIIRS prediction for synthetic aperture radar using a SAR General Image Quality Equation (GIQE) will provide SAR system designers with a tool for predicting the performance of various SAR modes (detection and tracking, coherent change detection, super-resolution and ATR processing, interferometric imaging, etc.) prior to actually building the SAR. The effect of this SAR GIQE will be the ability to predict functional performance of a SAR design across both employment and scenario, thereby allowing design and procurement decisions guided by the functions the SAR supports; it will also reveal the capabilities, limitations, and sensitivities critical to determining the best use of sensor resources.

* Information listed above is at the time of submission. *

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