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Compressed Sensing mm-Wave SAR for Non-Destructive Testing Applications Using Multiple Weighted Side Information.

Mathias Becquaert1,2, Edison Cristofani3,4, Huynh Van Luong5

  • 1CISS Department, Royal Military Academy, 30 Av. de la Renaissance, B-1000 Brussels, Belgium. mathias.becquaert@rma.ac.be.

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Summary
This summary is machine-generated.

This study introduces a new method for millimeter-wave Synthetic Aperture Radar (SAR) sensing using weighted side information to improve compressed sensing efficiency. The technique reconstructs high-quality SAR images even with low-quality data and significantly below Nyquist rates.

Keywords:
additive manufacturingcompressed sensingmm-wave sensingnon-destructive testingside informationsynthetic aperture radar

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Non-Destructive Testing

Background:

  • Compressed sensing (CS) in millimeter-wave (mm-wave) Synthetic Aperture Radar (SAR) sensing faces challenges with efficiency and data quality.
  • Utilizing multiple side information sources can enhance SAR image reconstruction but is sensitive to information quality.

Purpose of the Study:

  • To develop an innovative strategy for enhancing compressed sensing efficiency in mm-wave SAR sensing.
  • To improve SAR image reconstruction robustness and quality using multiple weighted side information.
  • To validate the approach on synthetic and real non-destructive testing (NDT) data.

Main Methods:

  • An algorithm was developed to autonomously assign weights to side information components and sources.
  • The method was tested on synthetic data and real NDT measurements of a 3D-printed object with defects.
  • Multiple previous SAR images with varying degrees of similarity were used as side information.

Main Results:

  • The algorithm demonstrated robustness against poor quality side information by exploiting relevant components.
  • High-quality SAR image reconstruction was achieved at subsampling rates significantly below the Nyquist rate.
  • The method proved more robust for low-quality side information compared to coherent background subtraction.

Conclusions:

  • The proposed weighted side information strategy significantly enhances compressed sensing efficiency in mm-wave SAR.
  • The algorithm offers a robust solution for SAR image reconstruction, particularly in NDT applications with limited or noisy data.
  • This approach enables high-fidelity imaging at reduced sampling rates, advancing SAR technology.