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2018 | Buch

Introduction and Motivation Kapitel lesen Erstes Kapitel lesen

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

verfasst von: Dr. Michael Leigsnering

Verlag: Springer International Publishing

Buchreihe : Springer Theses

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

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.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction and Motivation
Abstract
The idea of “X-ray vision”, i.e., the ability to see through walls or other visually opaque obstacles, has been popularized in many science fiction stories and comic books, most notably Superman. From a scientific perspective, real X-rays are not well-suited for this purpose as they are absorbed by walls and pass through possible objects of interest.
Michael Leigsnering
Chapter 2. Fundamentals of Compressive Sensing
Abstract
One of the most important concepts in signal processing is clearly the Shannon/Nyquist sampling theory (Shannon Proc IRE 37:10–21, 1949 [Sha49]). Its states that signals have to be sampled at twice their bandwidth to achieve perfect reconstruction. Nearly all of today’s data acquisition schemes are based on this theory. However, it is known that the Nyquist rate is a sufficient, but not a necessary condition for perfect reconstruction (Baraniuk et al. IEEE Signal Process. Mag. 25:12–13, 2008 [BCNV08]).
Michael Leigsnering
Chapter 3. Signal Model
Abstract
In this chapter, a forward scattering model is developed in order to describe the scattered Electro-Magnetic (EM) field from the targets inside the building. If the building layout and imaging geometry is known, this problem can be exactly solved by using Maxwell’s equations.
Michael Leigsnering
Chapter 4. Sparsity-Based Multipath Exploitation
Abstract
This chapter focuses on sparse reconstruction of targets in an indoor environment. Due to the front wall and surrounding scatterers, multipath propagation arises which is exploited to improve reconstruction results. The sparsity of the scene and the structure therein is leveraged to obtain a clean image from few measurements. Throughout this chapter, perfect knowledge of the room geometry is assumed and suppression of any wall or corner returns is required.
Michael Leigsnering
Chapter 5. Mitigating Wall Effects and Uncertainties
Abstract
This chapter deals with additional effects related to the building walls that have not been discussed yet.
Michael Leigsnering
Chapter 6. Conclusions and Outlook
Abstract
In this thesis, the problem of multipath propagation in Through-the-Wall Radar Imaging (TWRI) has been considered from a sparse reconstruction perspective. Compressive Sensing (CS) allows for excellent imaging results in scenarios with limited measurements of the scene. Utilizing a ray-tracing model for the propagation of the electromagnetic waves, multipath has been exploited in the image formation. CS-based multipath exploitation methods have been proposed which yield highly-resolved and artifact-free images of stationary and moving targets. Adverse effects related to reflections from the building structure have been tackled using joint reconstruction approaches.
Michael Leigsnering
Backmatter
Metadaten
Titel
Sparsity-Based Multipath Exploitation for Through-the-Wall Radar Imaging
verfasst von
Dr. Michael Leigsnering
Copyright-Jahr
2018
Electronic ISBN
978-3-319-74283-0
Print ISBN
978-3-319-74282-3
DOI
https://doi.org/10.1007/978-3-319-74283-0

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