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.

URSI_GASS_2011_short.pdf

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．