Computational Polarimetric Microwave Imaging

Thomas Fromenteze, Okan Yurduseven, Michael Boyarsky, Jonah Gollub, Daniel Marks, David Smith

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)
186 Downloads (Pure)


We propose a polarimetric microwave imaging technique that exploits recent advances in computational imaging. We utilize a frequency-diverse cavity-backed metasurface, allowing us to demonstrate high-resolution polarimetric imaging using a single transceiver and frequency sweep over the operational microwave bandwidth. The frequency-diverse metasurface imager greatly simplifies the system architecture compared with active arrays and other conventional microwave imaging approaches. We further develop the theoretical framework for computational polarimetric imaging and validate the approach experimentally using a multi-modal leaky cavity. The scalar approximation for the interaction between the radiated waves and the target— often applied in microwave computational imaging schemes—is thus extended to retrieve the susceptibility tensors, and hence provides additional information about the targets. Computational polarimetry has relevance for existing systems in the field that extract polarimetric imagery, and particular for ground observation. A growing number of short-range microwave imaging applications can also notably benefit from computational polarimetry, particularly for imaging objects that are difficult to reconstruct when assuming scalar estimations.
Original languageEnglish
Pages (from-to)1-19
JournalOptics Express
Issue number22
Publication statusPublished - 24 Oct 2017


  • Polarimetric Imaging
  • Computational Imaging
  • inverse problem
  • Imaging
  • Metasurfaces


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