Adaptive radar detection :: model-based, data-driven and hybrid approaches /
This book shows you how to adopt data-driven techniques for the problem of radar detection, both per se and in combination with model-based approaches. In particular, the focus is on space-time adaptive target detection against a background of interference consisting of clutter, possible jammers, an...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
[United States] :
Artech,
2022.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | This book shows you how to adopt data-driven techniques for the problem of radar detection, both per se and in combination with model-based approaches. In particular, the focus is on space-time adaptive target detection against a background of interference consisting of clutter, possible jammers, and noise. It is a handy, concise reference for many classic (model-based) adaptive radar detection schemes as well as the most popular machine learning techniques (including deep neural networks) and helps you identify suitable data-driven approaches for radar detection and the main related issues. You⁰́₉ll learn how data-driven tools relate to, and can be coupled or hybridized with, traditional adaptive detection statistics; understand fundamental concepts, schemes, and algorithms from statistical learning, classification, and neural networks domains. The book also walks you through how these concepts and schemes have been adapted for the problem of radar detection in the literature and provides you with a methodological guide for the design, illustrating different possible strategies. You⁰́₉ll be equipped to develop a unified view, under which you can exploit the new possibilities of the data-driven approach even using simulated data. This book is an excellent resource for Radar professionals and industrial researchers, postgraduate students in electrical engineering and the academic community. |
| Beschreibung: | 1 online resource |
| ISBN: | 9781630819019 1630819018 |
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| id | ZDB-4-EBA-on1357151165 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-27T13:30:40Z |
| institution | BVB |
| isbn | 9781630819019 1630819018 |
| language | English |
| oclc_num | 1357151165 |
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| spelling | Coluccia, Angelo, author. Adaptive radar detection : model-based, data-driven and hybrid approaches / Angelo Coluccia. [United States] : Artech, 2022. 1 online resource text txt rdacontent computer c rdamedia online resource cr rdacarrier This book shows you how to adopt data-driven techniques for the problem of radar detection, both per se and in combination with model-based approaches. In particular, the focus is on space-time adaptive target detection against a background of interference consisting of clutter, possible jammers, and noise. It is a handy, concise reference for many classic (model-based) adaptive radar detection schemes as well as the most popular machine learning techniques (including deep neural networks) and helps you identify suitable data-driven approaches for radar detection and the main related issues. You⁰́₉ll learn how data-driven tools relate to, and can be coupled or hybridized with, traditional adaptive detection statistics; understand fundamental concepts, schemes, and algorithms from statistical learning, classification, and neural networks domains. The book also walks you through how these concepts and schemes have been adapted for the problem of radar detection in the literature and provides you with a methodological guide for the design, illustrating different possible strategies. You⁰́₉ll be equipped to develop a unified view, under which you can exploit the new possibilities of the data-driven approach even using simulated data. This book is an excellent resource for Radar professionals and industrial researchers, postgraduate students in electrical engineering and the academic community. Title details screen. Radar Automatic detection. http://id.loc.gov/authorities/subjects/sh85110296 Radar Détection automatique. Radar Automatic detection fast Print version: 163081900X 9781630819002 (OCoLC)1339054951 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=3534281 Volltext |
| spellingShingle | Coluccia, Angelo Adaptive radar detection : model-based, data-driven and hybrid approaches / Radar Automatic detection. http://id.loc.gov/authorities/subjects/sh85110296 Radar Détection automatique. Radar Automatic detection fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85110296 |
| title | Adaptive radar detection : model-based, data-driven and hybrid approaches / |
| title_auth | Adaptive radar detection : model-based, data-driven and hybrid approaches / |
| title_exact_search | Adaptive radar detection : model-based, data-driven and hybrid approaches / |
| title_full | Adaptive radar detection : model-based, data-driven and hybrid approaches / Angelo Coluccia. |
| title_fullStr | Adaptive radar detection : model-based, data-driven and hybrid approaches / Angelo Coluccia. |
| title_full_unstemmed | Adaptive radar detection : model-based, data-driven and hybrid approaches / Angelo Coluccia. |
| title_short | Adaptive radar detection : |
| title_sort | adaptive radar detection model based data driven and hybrid approaches |
| title_sub | model-based, data-driven and hybrid approaches / |
| topic | Radar Automatic detection. http://id.loc.gov/authorities/subjects/sh85110296 Radar Détection automatique. Radar Automatic detection fast |
| topic_facet | Radar Automatic detection. Radar Détection automatique. Radar Automatic detection |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=3534281 |
| work_keys_str_mv | AT colucciaangelo adaptiveradardetectionmodelbaseddatadrivenandhybridapproaches |