© 2018

Sparsity-Based Multipath Exploitation for Through-the-Wall Radar Imaging


Part of the Springer Theses book series (Springer Theses)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Michael Leigsnering
    Pages 1-8
  3. Michael Leigsnering
    Pages 9-19
  4. Michael Leigsnering
    Pages 21-37
  5. Michael Leigsnering
    Pages 39-76
  6. Michael Leigsnering
    Pages 77-97
  7. Michael Leigsnering
    Pages 99-103
  8. Back Matter
    Pages 105-108

About this book


This thesis reports on sparsity-based multipath exploitation methods for through-the-wall radar imaging. Multipath creates ambiguities in the measurements provoking unwanted ghost targets in the image. This book describes sparse reconstruction methods that are not only suppressing the ghost targets, but using multipath to one’s advantage. With adopting the compressive sensing principle, fewer measurements are required for image reconstruction as compared to conventional techniques. The book describes the development of a comprehensive signal model and some associated reconstruction methods that can deal with many relevant scenarios, such as clutter from building structures, secondary reflections from interior walls, as well as stationary and moving targets, in urban radar imaging. The described methods are evaluated here using simulated as well as measured data from semi-controlled laboratory experiments.


Wall Location Estimation Dictionary Learning Multipath Exploitation Compressive Sensing Sparse Reconstruction Target Velocity Estimation Wall Clutter Mitigation Multipath Model Ghost Target Suppression Sparse Representations Compressed Sampling Front Wall Reverberations Wall Ringing Urban Radar TWRI Target Reconstruction Near- Field Imaging

Authors and affiliations

  1. 1.Signal Processing GroupTechnische Universität DarmstadtDarmstadtGermany

Bibliographic information

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