Compressed sensing mm-wave SAR for non-destructive testing applications using multiple weighted side information

Mathias Becquaert, Edison Cristofani, Huynh Van Luong, Marijke Vandewal, Johan Stiens, Nikos Deligiannis

Research output: Contribution to journalArticlepeer-review

Abstract

This work explores an innovative strategy for increasing the efficiency of compressed sensing applied on mm-wave SAR sensing using multiple weighted side information. The approach is tested on synthetic and on real non-destructive testing measurements performed on a 3D-printed object with defects while taking advantage of multiple previous SAR images of the object with different degrees of similarity. The tested algorithm attributes autonomously weights to the side information at two levels: (1) between the components inside the side information and (2) between the different side information. The reconstruction is thereby almost immune to poor quality side information while exploiting the relevant components hidden inside the added side information. The presented results prove that, in contrast to common compressed sensing, good SAR image reconstruction is achieved at subsampling rates far below the Nyquist rate. Moreover, the algorithm is shown to be much more robust for low quality side information compared to coherent background subtraction.

Original languageEnglish
Article number1761
JournalSensors (Switzerland)
Volume18
Issue number6
DOIs
Publication statusPublished - Jun 2018

Keywords

  • Additive manufacturing
  • Compressed sensing
  • Mm-wave sensing
  • Non-destructive testing
  • Side information
  • Synthetic aperture radar

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