1 INTRODUCTION

Recent developments in Artificial Intelligence (AI) and the accessibility of cost-effective radar hardware have transformed various sectors, including e-healthcare, smart cities, and critical infrastructures. AI holds immense potential for enhancing radar technology. However, there are significant challenges hindering its adoption in this domain. These challenges encompass Radar Data Accessibility, which involves limited access to radar data for training AI models due to low sample availability. Data Labelling, requiring domain-specific expertise, and Data Pre-processing, aimed at selecting the best radar data representation for AI applications, are complex and vital steps. Additionally, integrating an AI framework into radar hardware, whether using pre-trained or custom models, presents a major obstacle. This special issue focuses on research, articles, and experiments that bridge the gap between radar hardware and AI frameworks, addressing these critical challenges.

中文翻译：

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客座社论：人工智能辅助雷达传感应用的进展

1 简介

人工智能 (AI) 的最新发展和具有成本效益的雷达硬件的普及已经改变了各个领域，包括电子医疗保健、智能城市和关键基础设施。人工智能在增强雷达技术方面具有巨大潜力。然而，存在重大挑战阻碍其在该领域的采用。这些挑战包括雷达数据可访问性，由于样本可用性低，用于训练人工智能模型的雷达数据访问受到限制。数据标记需要特定领域的专业知识，数据预处理旨在为人工智能应用选择最佳的雷达数据表示，是复杂而重要的步骤。此外，无论是使用预训练模型还是定制模型，将人工智能框架集成到雷达硬件中都是一个主要障碍。本期特刊重点关注弥合雷达硬件和人工智能框架之间差距、解决这些关键挑战的研究、文章和实验。