RADLAB Seminar

Synthetic Aperature Radar

Dr. Sean McCarthy

Synthetic aperture radar (SAR) is an all weather sensor that has provided breakthrough remote sensing capabilities for both civilian and military applications, SAR differs from other real- aperture sensors in that it achieves fine resolution using signal processing techniques that are based on certain assumptions about the relative dynamics between the sensor and the scene. When these assumptions are violated, the quality of the SAR imagery degrades, impacting its interpretability.

This paper describes the development of a simulation testbed for evaluating the effects of SAR-specific error sources on image quality, including effects that originate with the sensor (e.g. system noise, uncompensated motion), as well as effects that originate in the scene (e.g. target motion, wind-blown trees). The simulation generates synthetic video phase history and can accommodate a variety of sensor collection trajectories, acquisition geometries, and image formation options. The simulation approach will be described, example outputs will be shown, and initial results relating simulation inputs to image quality measures will be presented.

Sean McCarthy received his B.S.E.E. from Texas A&M University in 1996 and his M.S.E.E. from the University of Florida 2004. From 1996-1998 he was employed with Lockheed Martin Astronautics Denver, CO and from 1998-2004 he worked at Raytheon in St. Petersburg, FL. Since 2004 he has been working as an Image & Signal Processing Engineer with the SAIC Ann Arbor Research & Development Center.

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