Compressive sensing and adaptive sampling applied to millimeter wave inverse synthetic aperture imaging.

Published

Journal Article

In order to improve speed and efficiency over traditional scanning methods, a Bayesian compressive sensing algorithm using adaptive spatial sampling is developed for single detector millimeter wave synthetic aperture imaging. The application of this algorithm is compared to random sampling to demonstrate that the adaptive algorithm converges faster for simple targets and generates more reliable reconstructions for complex targets.

Full Text

Duke Authors

Cited Authors

  • Zhu, R; Richard, JT; Brady, DJ; Marks, DL; Everitt, HO

Published Date

  • February 2017

Published In

Volume / Issue

  • 25 / 3

Start / End Page

  • 2270 - 2284

PubMed ID

  • 29519075

Pubmed Central ID

  • 29519075

Electronic International Standard Serial Number (EISSN)

  • 1094-4087

International Standard Serial Number (ISSN)

  • 1094-4087

Digital Object Identifier (DOI)

  • 10.1364/oe.25.002270

Language

  • eng