| 书目名称 | Sparsity-Based Multipath Exploitation for Through-the-Wall Radar Imaging |
| 编辑 | Michael Leigsnering |
| 视频video | |
| 概述 | Nominated as an outstanding PhD thesis by the Technische Universität Darmstadt, Germany.Combines the fields of through-the-wall radar imaging and compressive sensing.Demonstrates how image quality can |
| 丛书名称 | Springer Theses |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2018 |
| 关键词 | Wall Location Estimation; Dictionary Learning; Multipath Exploitation; Compressive Sensing; Sparse Recon |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-74283-0 |
| isbn_softcover | 978-3-319-89274-0 |
| isbn_ebook | 978-3-319-74283-0Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer International Publishing AG 2018 |
发表于 2025-3-21 18:20:11
