Monday May 4 4:00 - 4:50 PM Kelley 1001
James H. McClellan Professor Center for Signal & Image Processing Georgia Tech Compressive Sensing Data Acquisition and Imaging for GPRs New data acquisition and imaging strategies are presented for ground penetrating radars (GPRs) used in subsurface imaging. Both stepped- frequency continuous-wave (SFCW) and impulse GPRs are considered. When the target space is sparse, i.e., a small number of point like targets, the theory of compressive sensing (CS) tells us that making measurements at only a small number of random frequencies (or times) is sufficient to construct an image of the target space by solving a convex optimization problem which enforces sparsity through L1 minimization. Random spatial sampling of the synthetic aperture can also be performed as part of this data acquisition method, which greatly reduces the GPR acquisition time at the expense of higher computational costs. Imaging results for both simulated and experimental GPR data exhibit less clutter and better resolution than the standard migration and backprojection methods. Biography: James McClellan (Ph.D. in Electrical and Computer Engineering, Rice University, 1973) holds the John & Marilu McCarty Chair as a Professor of Electrical and Computer Engineering at Georgia Tech, where he is also the head of the Center for Signal & Image Processing (CSIP). His thesis research on digital filters produced an algorithm and computer program that became a standard method for FIR digital filter design, and also introduced a transformation technique that simplifies the design of 2-D filters which find application in image processing and seismic processing for oil exploration. For this work, Dr. McClellan received the IEEE Jack S. Kilby Signal Processing medal in 2004 together with his thesis advisor, Dr. T. W. Parks. He is a Fellow of the IEEE. From the IEEE Signal Processing Society, he has received the Technical Achievement Award (1987), the Society Award (1996), and the Education Award (2001).
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