Adaptive Radar Detection Model Based Data Driven And Hybrid Approaches


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Adaptive Radar Detection


Adaptive Radar Detection

Author: Angelo Coluccia

language: en

Publisher: Artech House Publishers

Release Date: 2022-11-30


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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. You'll 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. You'll 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.

Adaptive Radar Detection: Model-Based, Data-Driven and Hybrid Approaches


Adaptive Radar Detection: Model-Based, Data-Driven and Hybrid Approaches

Author: Angelo Coluccia

language: en

Publisher: Artech House

Release Date: 2022-11-30


DOWNLOAD





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. You’ll 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. You’ll 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.

Radar and EW Modeling in MATLAB and Simulink


Radar and EW Modeling in MATLAB and Simulink

Author: Carlos A. Dávila

language: en

Publisher: Artech House

Release Date: 2023-10-31


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This resource covers basic concepts and modeling examples for the three “pillars” of EW: Electronic Attack (EA) systems, Electronic Protection (EP) techniques, and Electronic Support (ES). It develops techniques for the modeling and simulation (M&S) of modern radar and electronic warfare (EW) systems and reviews radar principles, including the radar equation. M&S techniques are introduced, and example models developed in MATLAB and Simulink are presented and discussed in detail. These individual models are combined to create a full end-to-end engineering engagement simulation between a pulse-Doppler radar and a target. The radar-target engagement model is extended to include jamming models and is used to illustrate the interaction between radar and jamming signals and the impact on radar detection and tracking. In addition, several classic EA techniques are introduced and modeled, and the effects on radar performance are explored. This book is a valuable resource for engineers, scientists, and managers who are involved in the design, development, or testing of radar and EW systems. It provides a comprehensive overview of the M&S techniques that are used in these systems, and the book's many examples and case studies provide a solid foundation for understanding how these techniques can be applied in practice.