AI in Radar Signal Processing

Dear Colleagues,

In recent years, the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques with radar technology has led to significant advances in radar signal processing, system design, and application development. This Special Issue aims to provide a comprehensive overview of current research progress and emerging trends in AI-enabled radar systems, highlighting both their transformative potential and the challenges that remain.

The focus of this Special Issue is on learning-based methods for radar processing and applications, encompassing both algorithmic innovations and system-level considerations. The scope includes, but is not limited to, AI and ML approaches for radar detection, tracking, classification, and imaging; deep learning and reinforcement learning techniques for adaptive and cognitive radar; radar resource management and waveform optimization; and AI-assisted radar hardware and subsystem design. In addition, the collection covers a wide range of application domains, from automotive sensing, human activity and gesture recognition, and healthcare monitoring to more traditional areas such as radar surveillance and remote sensing.

The purpose of this Special Issue is to serve as a dedicated platform for disseminating state-of-the-art research and fostering interdisciplinary collaboration between the radar and AI communities. By bringing together contributions from diverse application areas and methodological perspectives, this issue seeks to bridge the gap between data-driven learning approaches and classical model-based radar theory, promoting solutions that are not only accurate but also robust, interpretable, and suitable for real-world deployment.

While the existing literature has extensively explored AI techniques for specific radar tasks—most notably automatic target recognition—many studies remain narrowly focused on isolated problems or rely on idealized assumptions and proprietary datasets. This Special Issue aims to supplement the current body of work by addressing broader system-level challenges, including data scarcity and confidentiality, generalization across operating conditions, and the need for explainable and trustworthy AI in safety-critical domains such as automotive and defense. By consolidating these perspectives in a single collection, this Special Issue is expected to provide valuable insights, identify open research directions, and accelerate the responsible adoption of AI in next-generation radar systems.

We look forward to hearing from you.

Dr. Sen Yuan
Prof. Dr. Jianping Wang
Dr. Deqing Mao
Dr. Ronny Guendel
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• artificial intelligence for radar
• radar signal processing
• adaptive and cognitive radar
• deep learning
• automotive radar
• human activity and gesture recognition
• healthcare and biomedical radar
• human-centric radar applications