Description: Compressed sensing, a method which relies on sparsity to reconstruct signals with relatively few measurements, has
the potential to greatly improve observation of distributed radar targets. We extend the theoretical work of others by
investigating the practical problems of implementing this approach for distributed targets, first examining a discrete
linear radar model suitable for compressed sensing and then discussing an example of this technique used on existing
data. Potential benefits include higher possible range resolution, complete filtering of noise without sidelobes or
artifacts, and the ability to identify different Doppler shifts within the same range window of a single pulse.
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URSI_GASS_2011_short.pdf
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