Multi-frequency subspace migration for imaging of perfectly conducting, arc-like cracks

TL;DR

This paper analyzes the structure of multi-frequency subspace migration imaging functional for detecting arc-like cracks, revealing its mathematical properties and proposing an improved weighted version for better imaging resolution.

Contribution

It provides a theoretical analysis of the imaging functional structure, explaining the enhancement from multi-frequency data, and introduces a weighted multi-frequency approach for improved imaging.

Findings

Imaging functional can be expressed as a linear combination of Bessel functions.

Multi-frequency data enhances imaging resolution.

The weighted multi-frequency functional improves detection of cracks.

Abstract

Multi-frequency subspace migration imaging technique are usually adopted for the non-iterative imaging of unknown electromagnetic targets such as cracks in the concrete walls or bridges, anti-personnel mines in the ground, etc. in the inverse scattering problems. It is confirmed that this technique is very fast, effective, robust, and can be applied not only full- but also limited-view inverse problems if suitable number of incident and corresponding scattered field are applied and collected. But in many works, the application of such technique is somehow heuristic. Under the motivation of such heuristic application, this contribution analyzes the structure of imaging functional employed in the subspace migration imaging technique in two-dimensional inverse scattering when the unknown target is arbitrary shaped, arc-like perfectly conducting cracks located in the homogeneous two-dimensional space. Opposite to the Statistical approach based on the Statistical Hypothesis Testing, our approach is based on the fact that subspace migration imaging functional can be expressed by a linear combination of Bessel functions of integer order of the first kind. This is based on the structure of the Multi-Static Response (MSR) matrix collected in the far-field at nonzero frequency in either Transverse Magnetic (TM) mode or Transverse Electric (TE) mode. Explored expression of imaging functionals gives us certain properties of subspace migration and an answer of why multi-frequency enhances imaging resolution. Particularly, we carefully analyze the subspace migration and confirm some properties of imaging when a small number of incident field is applied. Consequently, we simply introduce a weighted multi-frequency imaging functional and confirm that which is an improved version of subspace migration in TM mode.