Characterizing SAR image exploitation as a function of operating conditions

Matthew Scherreik; Adam Nolan; Shaun Stephens; Lori Westerkamp; Edmund Zelnio

doi:10.1117/12.2619263

31 May 2022 Characterizing SAR image exploitation as a function of operating conditions

Matthew Scherreik, Adam Nolan, Shaun Stephens, Lori Westerkamp, Edmund Zelnio

Author Affiliations +

Proceedings Volume 12095, Algorithms for Synthetic Aperture Radar Imagery XXIX; 1209509 (2022) https://doi.org/10.1117/12.2619263
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

We propose methods to improve the use of synthetic data for characterizing SAR image exploitation in terms of various operating conditions (OCs). More specifically, we describe tools that simulate statistically relevant samples of SAR imagery and classify the resulting imagery via a baseline algorithm. The associated OC generation, user interfaces, databasing of OCs, classification, analysis, and visualization have been containerized and ported to run on the DoD Supercomputing Resource Centers. To demonstrate our workflow, we present four case studies with the quantized grayscale matching algorithm. The work described here provides a foundation to support future developments in multi-look and multi-sensor fusion.

Conference Presentation

Citation Download Citation

Matthew Scherreik, Adam Nolan, Shaun Stephens, Lori Westerkamp, and Edmund Zelnio "Characterizing SAR image exploitation as a function of operating conditions", Proc. SPIE 12095, Algorithms for Synthetic Aperture Radar Imagery XXIX, 1209509 (31 May 2022); https://doi.org/10.1117/12.2619263

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