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Author Leigsnering, Michael,
Title Sparsity-based multipath exploitation for through-the-wall radar imaging / Michael Leigsnering.
Imprint Cham, Switzerland : Springer, 2018.

View online
View online
Author Leigsnering, Michael,
Series Springer theses, 2190-5053
Springer theses. 2190-5053
Subject Compressed sensing (Telecommunication)
Description 1 online resource (xx, 108 pages) : illustrations (some color).
Note "Doctoral thesis accepted by Technische Universitat Darmstadt, Darmstadt, Germany."
Bibliography Note Includes bibliographical references.
Contents Intro; Supervisora#x80;#x99;s Foreword; Supervisora#x80;#x99;s Foreword; Acknowledgements; Contents; Acronyms; Symbols; 1 Introduction and Motivation; 1.1 Motivation; 1.2 State-of-the-Art; 1.3 Contributions; 1.4 Thesis Overview; References; 2 Fundamentals of Compressive Sensing; 2.1 Assumptions and Conditions for Reconstruction; 2.1.1 Sensing on Linear Bases; 2.1.2 Sparsity; 2.1.3 Conditions on the Measurement Matrix; 2.2 Reconstruction Algorithms; 2.2.1 Optimization-Based Approaches; 2.2.2 Greedy Approaches; 2.3 Application to Through-the-Wall Radar Imaging; References; 3 Signal Model.
3.1 Ultra-Wideband Signal Model3.2 Stepped-Frequency Signal Model; 3.3 Multipath Propagation; 3.3.1 Direct Path and Wall Ringing Multipath; 3.3.2 Interior Wall Multipath; 3.3.3 Bistatic Received Signal Model; 3.4 Direct Wall Reflections; 3.5 Efficient Sampling Schemes; 3.5.1 Ultra-Wideband Pulse Radar; 3.5.2 Stepped-Frequency Radar; References; 4 Sparsity-Based Multipath Exploitation; 4.1 Motivation; 4.2 Conventional Image Formation; 4.3 Stationary Targets; 4.3.1 Conventional Sparse Reconstruction; 4.3.2 Group Sparse Reconstruction; 4.3.3 Sparse Reconstruction with Overlapping Groups.
4.3.4 Simulation and Experimental Results4.4 Stationary and Moving Targets; 4.4.1 Apparent Doppler Speed; 4.4.2 Joint Target Location and Velocity Estimation; 4.4.3 Target Location Reconstruction with Subsequent Velocity Estimation; 4.4.4 Simulation and Experimental Results; 4.5 Distributed Radar; 4.5.1 Multiple Radar Unit Model; 4.5.2 Dictionary Analysis; 4.5.3 Joint Group Sparse Reconstruction; 4.5.4 Simulation Results; 4.6 Conclusions; References; 5 Mitigating Wall Effects and Uncertainties; 5.1 Motivation; 5.2 Front Wall Reflections; 5.2.1 Wall Reflection Model.
5.2.2 Separate Reconstruction5.2.3 Joint Group Sparse Reconstruction; 5.2.4 Joint Overlapping Group Sparse Reconstruction; 5.2.5 Simulation and Experimental Results; 5.3 Wall Location Correction; 5.3.1 Multipath Model Including Wall Position Errors; 5.3.2 Joint Sparse Reconstruction and Wall Position Estimation; 5.3.3 Simulation and Experimental Results; 5.4 Conclusions; References; 6 Conclusions and Outlook; 6.1 Conclusions; 6.1.1 Multipath Model; 6.1.2 Sparsity-Based Multipath Exploitation; 6.1.3 Mitigating Wall Effects and Uncertainties; 6.2 Outlook; 6.2.1 Signal Model.
6.2.2 Sparsity-Based Multipath Exploitation6.2.3 Sparse Reconstruction with Parameter Uncertainties; References; A; A.1 Complex Amplitude Derivation; A.2 Justification of the Invariance of Complex Amplitude Across the Array; Appendix Curriculum Vitae.
Summary 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.
Note Online resource; title from PDF title page (SpringerLink, viewed February 20, 2018).
ISBN 9783319742830 (electronic bk.)
3319742833 (electronic bk.)
9783319742823 (print)
ISBN/ISSN 10.1007/978-3-319-74283-0
OCLC # 1023626932
Additional Format Print version: Leigsnering, Michael. Sparsity-based multipath exploitation for through-the-wall radar imaging. Cham, Switzerland : Springer, 2018 3319742825 9783319742823 (OCoLC)1016050322

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