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Microwave Imaging

ISBN: 978-0-470-27800-0
285 pages
April 2010
Microwave Imaging (0470278005) cover image
An introduction to the most relevant theoretical and algorithmic aspects of modern microwave imaging approaches

Microwave imaging—a technique used in sensing a given scene by means of interrogating microwaves—has recently proven its usefulness in providing excellent diagnostic capabilities in several areas, including civil and industrial engineering, nondestructive testing and evaluation, geophysical prospecting, and biomedical engineering.

Microwave Imaging offers comprehensive descriptions of the most important techniques so far proposed for short-range microwave imaging—including reconstruction procedures and imaging systems and apparatus—enabling the reader to use microwaves for diagnostic purposes in a wide range of applications. This hands-on resource features:

  • A review of the electromagnetic inverse scattering problem formulation, written from an engineering perspective and with notations

  • The most effective reconstruction techniques based on diffracted waves, including time- and frequency-domain methods, as well as deterministic and stochastic space-domain procedures

  • Currently proposed imaging apparatus, aimed at fast and accurate measurements of the scattered field data

  • Insight on near field probes, microwave axial tomographs, and microwave cameras and scanners

  • A discussion of practical applications with detailed descriptions and discussions of several specific examples (e.g., materials evaluation, crack detection, inspection of civil and industrial structures, subsurface detection, and medical applications)

  • A look at emerging techniques and future trends

Microwave Imaging is a practical resource for engineers, scientists, researchers, and professors in the fields of civil and industrial engineering, nondestructive testing and evaluation, geophysical prospecting, and biomedical engineering.

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1 Introduction.

2 Electromagnetic Scattering.

2.1 Maxwell’s Equations.

2.2 Interface Conditions.

2.3 Constitutive Equations.

2.4 Wave Equations and Their Solutions.

2.5 Volume Scattering by Dielectric Targets.

2.6 Volume Equivalence Principle.

2.7 Integral Equations.

2.8 Surface Scattering by Perfectly Electric Conducting Targets.

References.

3 The Electromagnetic Inverse Scattering Problem.

3.1 Introduction.

3.2 Three-Dimensional Inverse Scattering.

3.3 Two-Dimensional Inverse Scattering.

3.4 Discretization of the Continuous Model.

3.5 Scattering by Canonical Objects: The Case of Multilayer Elliptic Cylinders.

References.

4 Imaging Configurations and Model Approximations.

4.1 Objectives of the Reconstruction.

4.2 Multiillumination Approaches.

4.3 Tomographic Confi gurations.

4.4 Scanning Confi gurations.

4.5 Confi gurations for Buried-Object Detection.

4.6 Born-Type Approximations.

4.7 Extended Born Approximation.

4.8 Rytov Approximation.

4.9 Kirchhoff Approximation.

4.10 Green's Function for Inhomogeneous Structures.

References.

5 Qualitative Reconstruction Methods.

5.1 Introduction.

5.2 Generalized Solution of Linear Ill-Posed Problems.

5.3 Regularization Methods.

5.4 Singular Value Decomposition.

5.5 Singular Value Decomposition for Solving Linear Problems.

5.6 Regularized Solution of a Linear System Using Singular Value Decomposition.

5.7 Qualitative Methods for Object Localization and Shaping.

5.8 The Linear Sampling Method.

5.9 Synthetic Focusing Techniques.

5.10 Qualitative Methods for Imaging Based on Approximations.

5.11 Diffraction Tomography.

5.12 Inversion Approaches Based on Born-Like Approximations.

5.13 The Born Iterative Method.

5.14 Reconstruction of Equivalent Current Density.

References.

6 Quantitative Deterministic Reconstruction Methods.

6.1 Introduction.

6.2 Inexact Newton Methods.

6.3 The Truncated Landweber Method.

6.4 Inexact Newton Method for Electric Field Integral Equation Formulation.

6.5 Inexact Newton Method for Contrast Source Formulation.

6.6 The Distorted Born Iterative Method.

6.7 Inverse Scattering as an Optimization Problem.

6.8 Gradient-Based Methods.

References.

7 Quantitative Stochastic Reconstruction Methods.

7.1 Introduction.

7.2 Simulated Annealing.

7.3 The Genetic Algorithm.

7.4 The Differential Evolution Algorithm.

7.5 Particle Swarm Optimization.

7.6 Ant Colony Optimization.

7.7 Code Parallelization.

References.

8 Hybrid Approaches.

8.1 Introduction.

8.2 The Memetic Algorithm.

8.3 Linear Sampling Method and Ant Colony Optimization.

References.

9 Microwave Imaging Apparatuses and Systems.

9.1 Introduction.

9.2 Scanning Systems for Microwave Tomography.

9.3 Antennas for Microwave Imaging.

9.4 The Modulated Scattering Technique and Microwave Cameras.

References.

10 Applications of Microwave Imaging.

10.1 Civil and Industrial Applications.

10.2 Medical Applications of Microwave Imaging.

10.3 Shallow Subsurface Imaging.

References.

11 Microwave Imaging Strategies, Emerging Techniques, and Future Trends.

11.1 Introduction.

11.2 Potentialities and Limitations of Three-Dimensional Microwave Imaging.

11.3 Amplitude-Only Methods.

11.4 Support Vector Machines.

11.5 Metamaterials for Imaging Applications.

11.6 Through-Wall Imaging.

References.

INDEX.

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MATTEO PASTORINO, PhD, is a Professor of Electromagnetic Fields and the Director of the Department of Biophysical and Electronic Engineering, University of Genoa, Italy. He teaches the university courses in electromagnetic fields and remote sensing and electromagnetic propagation. Professor Pastorino's main research interests are in the field of microwave and millimeter wave imaging, direct and inverse scattering problems, industrial and medical applications, smart antennas, and analytical and numerical methods in electromagnetism. He is the coauthor of more than 350 papers in international journals and proceedings of conferences.
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