English

A random matrix approach to detect defects in a strongly scattering polycrystal: how the memory effect can help overcome multiple scattering

Other Condensed Matter 2015-06-19 v1 Disordered Systems and Neural Networks Data Analysis, Statistics and Probability

Abstract

We report on ultrasonic imaging in a random heterogeneous medium. The goal is to detect flaws embedded deeply into a polycrystalline material. A 64-element array of piezoelectric transmitters/receivers at a central frequency of 5 MHz is used to capture the Green's matrix in a backscattering configuration. Because of multiple scattering, conventional imaging completely fails to detect the deepest flaws. We utilize a random matrix approach, taking advantage of the deterministic coherence of the backscattered wave-field which is characteristic of single scattering and related to the memory effect. This allows us to separate single and multiple scattering contributions. As a consequence, we show that flaws are detected beyond the conventional limit, as if multiple scattering had been overcome.

Keywords

Cite

@article{arxiv.1405.6526,
  title  = {A random matrix approach to detect defects in a strongly scattering polycrystal: how the memory effect can help overcome multiple scattering},
  author = {Sharfine Shahjahan and Alexandre Aubry and Fabienne Rupin and Bertrand Chassignole and Arnaud Derode},
  journal= {arXiv preprint arXiv:1405.6526},
  year   = {2015}
}

Comments

11 pages, 4 figures

R2 v1 2026-06-22T04:23:13.701Z