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1.1 Basic Concepts 3.1 STAP I 3.2 Super-Resolution 3.3 Clutter 3.4 SAR Intro
2.1 Bistatic 4.1 STAP II 4.2 SAR ATR 4.3 Pulse Compression 4.4 RCS
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3.2 Super-Resolution Techniques for Synthetic Aperture Radar

Instructors: Dr. S. Lawrence (Larry) Marple, Jr. (Orincon Corp, San Diego) and Dr. Stuart R. DeGraaf (Northrop Grumman, Baltimore)

Thursday April 25, 8:00 a.m. to 12:00 a.m.

Abstract

This tutorial offers an overview of a variety of proposed and practiced super-resolution techniques for SAR. The conceptual and mathematical foundations (nonparametric, parametric, subspace) for an alphabet soup of techniques, including classical FFT-based, AR, LP, MVM, RRMVM, HDI, ASR, SVA, superSVA, EV, MUSIC, PM, TKARLP, and PML, will be summarized. Issues, tradeoffs, artifacts, and implementation complexity will be a focus of the course. Other highlights include:

  • Fast computational algorithms
  • Algorithm implementation through use of decimation/mosaicking polyphase filters.
  • Nonclassified image comparison using simulated point scatterers, ERIM DCS data, Sandia STARLOS/MSTAR, and indoor RCS chamber data.
  • Movies showing signature stabilization or randomizing properties of algorithms.
  • Speckle reduction vs. resolution sharpening effect on detection and target separability.
  • Phase error sensitivity and autofocus issues.

Bios

Picture Coming Soon

S. Lawrence Marple Jr. received the B.S. and M.E.E. degrees from Rice University and the Engr. Deg. from Stanford University in electrical engineering. He is currently Chief Scientist of ORINCON Corporation in San Diego, CA, which is involved in DoD and intelligence sensor signal processing and target signature exploitation. He has 30 years of experience in the development and implementation of digital signal processing algorithms, software, and hardware for temporal, frequency, and spatial domain signals in sonar, radar, communications, intelligence, acoustic well logging, and ultrasound imaging. He has published widely in journals, such as the IEEE Signal Processing Transactions. He author of the text Digital Spectral Analysis (Prentice Hall, 1987) and a new signal analysis text (2003). He was elected a Fellow of the IEEE in 1989 for "contributions to the theory and application of spectral analysis in digital signal processing."


Picture Coming Soon Stuart R. DeGraaf (S'79-M'84) received the B.S. degree from Princeton University, Princeton, NJ in 1979, and the M.S. and Ph.D. degrees from Rice University, Houston, TX, in 1982 and 1984, respectively, all in electrical engineering. From 1985 to 1995, he was a Research Engineer at the Environmental Research Institute of Michigan, Ann Arbor, where he developed signal processing and automatic target detection and recognition algorithms for multi-channel SAR. Since 1995 he has been an Advisory Engineer at Northrop Grumman, Electronic Sensors and Systems Sector, Baltimore, MD. Dr. DeGraaf has published several articles discussing the application of 2-D spectral estimation techniques to radar imaging.


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