创新的深度学习方法在雷达目标识别领域取得了最先进的精度，使相关应用超越了人类的水平。

Novel deep learning approaches are achieving state-of-the-art accuracy in the area of radar target recognition, enabling applications beyond the scope of human-level performance.

本书提供了一个独特的关于雷达信号处理机器学习方面的介绍，这是所有科学家或工程师正在寻求应用的技术。

This book provides an introduction to the unique aspects of machine learning for radar signal processing that any scientist or engineer seeking to apply these technologies ought to be aware of.

本书开始于雷达系统和基本现象、机器学习原理，和训练深度神经网络（DNN）架构优化的三个介绍性章节。

The book begins with three introductory chapters on radar systems and phenomenology, machine learning principles, and optimization for training common deep neural network (DNN) architectures.

随后，本书总结了与不同领域表示相关的雷达特定问题，其中的雷达数据可呈现给DNN，并生成用于训练数据集扩充的合成数据。

Subsequently, the book summarizes radar-specific issues relating to the different domain representations in which radar data may be presented to DNNs and synthetic data generation for training dataset augmentation.

接下来的章节将重点介绍具体的雷达应用，涉及到微多普勒分析的DNN设计、基于SAR的自动目标识别、雷达遥感以及数据融合和图像重建等新兴领域。

Further chapters focus on specific radar applications, which relate to DNN design for micro-Doppler analysis, SAR-based automatic target recognition, radar remote sensing, and emerging fields, such as data fusion and image reconstruction.

本书由一位公认的专家编辑，并由一个国际作者团队做出贡献，提供了雷达和机器学习基础的介绍，然后继续探索在这个发展领域中的一系列技术、应用和挑战。

Edited by an acknowledged expert, and with contributions from an international team of authors, this book provides a solid introduction to the fundamentals of radar and machine learning, and then goes on to explore a range of technologies, applications and challenges in this developing field.

无论是雷达工程师寻求了解更多的深度学习，还是计算机科学家寻求探索机器学习的新应用，本书都是一个宝贵的资源。

This book is also a valuable resource for both radar engineers seeking to learn more about deep learning, as well as computer scientists who are seeking to explore novel applications of machine learning.

在一个射频应用日新月异的时代，这本书将是易于入门的将深度学习应用于雷达领域的资源。

In an era where the applications of RF sensing are multiplying by the day, this book serves as an easily accessible primer on the nuances of deep learning for radar applications.

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