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Название: Introduction to Synthetic Aperture Radar Using Python and MATLAB
Автор: Andy Harrison
Издательство: Artech House
Год: 2022
Страниц: 381
Язык: английский
Формат: pdf (true)
Размер: 166.0 MB
This comprehensive introduction to synthetic aperture radar (SAR) is a practical guide to the analysis, simulation, and design of SAR systems. The video eBook uses constructive examples and real-world collected datasets to demonstrate image registration and autofocus methods. Both two- and three-dimensional image formation algorithms are presented. Hardware, software, and environmental parameters are used to estimate performance limits for SAR operation and utilization. A set of Python and MATLAB software tools is included and provides you with an effective mechanism to analyze and predict SAR performance for various imaging scenarios and applications. Examples which use the software tools are provided at the end of each chapter to reinforce critical SAR imaging topics such as clutter-to-noise ratio, mapping rate, spatial resolution, Doppler bandwidth, pulse repetition frequency, and coherency. This is an excellent resource for engineering professionals working in areas of radar signal processing and imaging as well as students interested in studying SAR. The tool suite is written in the Python and MATLAB programming languages and gives the reader a mechanism to generate SAR images, predict the performance of SAR systems for various applications, and analyze images resulting from different scenarios.
Автор: Andy Harrison
Издательство: Artech House
Год: 2022
Страниц: 381
Язык: английский
Формат: pdf (true)
Размер: 166.0 MB
This comprehensive introduction to synthetic aperture radar (SAR) is a practical guide to the analysis, simulation, and design of SAR systems. The video eBook uses constructive examples and real-world collected datasets to demonstrate image registration and autofocus methods. Both two- and three-dimensional image formation algorithms are presented. Hardware, software, and environmental parameters are used to estimate performance limits for SAR operation and utilization. A set of Python and MATLAB software tools is included and provides you with an effective mechanism to analyze and predict SAR performance for various imaging scenarios and applications. Examples which use the software tools are provided at the end of each chapter to reinforce critical SAR imaging topics such as clutter-to-noise ratio, mapping rate, spatial resolution, Doppler bandwidth, pulse repetition frequency, and coherency. This is an excellent resource for engineering professionals working in areas of radar signal processing and imaging as well as students interested in studying SAR. The tool suite is written in the Python and MATLAB programming languages and gives the reader a mechanism to generate SAR images, predict the performance of SAR systems for various applications, and analyze images resulting from different scenarios.