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<HTML>
<CENTER><A HREF = "main.html">Return to Steve Plimpton's home page</A>
</CENTER>
<HR>
<H3>Image Processing - synthetic aperture radar analysis
</H3>
<P>Synthetic aperture radar (SAR) is a technique for taking extremely
high- resolution radar images, typically of ground features from an
airplane. In spotlight mode, the radar beam is focused on one patch of
ground as the aircraft flies from point A to point B. Returned signals
are collected continuously to create a high-resolution image
integrated over a very large aperture.
</P>
<CENTER><IMG SRC = "images/sar_airplane.gif">
</CENTER>
<P>Several stages of this procedure can benefit from the power of
parallel computing. I worked with several SAR experts at Sandia to
implement their computational algorithms on large parallel machines we
had at the time -- an nCUBE 2 and Connection Machine (CM-2). The SAR
group at Sandia ended up purchasing their own 1024-processor nCUBE 2
for research and day-to-day data processing because of the increased
throughput it provided.
</P>
<P>Several stages of the SAR data processing are discussed in the papers
below. The first is called "polar reformatting", which is to take a
large dataset (e.g. 16384 x 65536) which has been collected on a polar
grid (circular points in the figure) and accurately interpolate it to
a Cartesian grid (square points). This operation is performed in
reciprocal or phase space.
</P>
<CENTER><IMG SRC = "images/sar_reformat.gif">
</CENTER>
<P>This picture illustrates the input to the polar reformatting algorithm
and the result for a simple test pattern. When the polar data is
displayed on a Cartesian grid, straight lines appear bent; the
reformatting corrects for this effect.
</P>
<CENTER><IMG SRC = "images/sar_lines.gif">
</CENTER>
<P>The next stage is to perform a very large 2-d FFT to convert the SAR
data from phase space to real space. Our algorithmic work in parallel
FFTs is discussed <A HREF = "algorithms.html">here</A>. Basically it requires an all-to-all
matrix transpose sandwiched between 2 sets of 1-d FFTs. The 4 GB
aggregate memory of the nCUBE 2 (large at the time!) proved adequate
for performing this entire operation in-memory.
</P>
<P>Finally, the SAR image needs enhancement to correct for errors due to
effects like airplane motion and platform jitter. We implemented a
parallel version of the phase-gradient autofocus (PGA) algorithm
invented by my collaborators at Sandia. PGA has the advantages of
being automatic (requiring no user intervention), correcting phase
errors of all orders, and working on high and low signal-to-clutter
images. In our implementation PGA proceeds in 2 phases: first the
correction factors are computed for a subpatch of the overall image,
then the correction is applied repeatedly to all subpatches in the
entire image. The effect can be dramatic as illustrated in this data
set.
</P>
<CENTER><IMG SRC = "images/sar_tower.gif">
</CENTER>
<P>The photograph on the left is of a solar tower and mirror array at
Sandia. The as-collected radar image of the tower is shown on the
right. The images below are of the radar image after enhancement via
the PGA algorithm. The left image is after a few iterations of PGA;
the fully corrected image is on the right. Note that the radar shadow
cast by the tower onto the array of mirrors is now clearly visible, as
are the mirror corners and tie-downs (bright points). The latter are
very small features that SAR is capable of resolving due to their
sharp corners (high reflectivity).
</P>
<CENTER><IMG SRC = "images/sar_pga.gif">
</CENTER>
<P>Collaborators on this project:
</P>
<UL><LI> Gary Mastin, Sandia
<LI> Dennis Ghiglia, Sandia
</UL>
<HR>
<P>Details of the 3 stages of SAR data processing are described in these
papers. Parallel performance and scalability are discussed for the
nCUBE 2 and Connection Machine (CM-2) platforms.
</P>
<P><B>A Massively-Parallel Digital Processor for Spotlight
Synthetic-Aperture Radar</B>, G. A. Mastin, S. J. Plimpton, D. Ghiglia,
Int J of Supercomputer Applications, 7, 97-112
(1993). (<A HREF = "abstracts/ijsa93.html">abstract</A>)
</P>
<P><B>Synthetic Aperture Radar Image Processing on Parallel
Supercomputers</B>, S. J. Plimpton, G. A. Mastin, D. Ghiglia, in Proc of
Supercomputing '91, Albuquerque, NM, November 1991, p
446. (<A HREF = "abstracts/sc91.html">abstract</A>)
</P>
</HTML>