Target Recognition Based on Radar Imaging

Dear Colleagues,

Background introduction: Rapid developments in millimeter-wave radar, signal processing and artificial intelligence are greatly promoting modern intelligent sensing technology. Traditional radar systems mainly focus on target detection, localization and recognition. However, current practical scenarios require higher resolution, multi-dimensional perception and stronger anti-interference ability. Complex noise, multipath interference, dynamic environments and diverse target features still bring many difficulties to accurate radar sensing and information extraction.

In recent years, emerging algorithms in digital signal processing, image reconstruction, deep learning and multimodal fusion have provided effective solutions for radar performance optimization. More importantly, radar-related sensing theories and intelligent methods have gradually expanded to many interdisciplinary fields. The cross integration of radar technology, computer vision and data-driven modeling has become a popular research trend, which brings new opportunities for both academic exploration and industrial applications.

Aim and Scope: This Special Issue aims to provide a broad interdisciplinary platform for recent advances in digital signal processing, image processing, intelligent sensing, data-driven modeling, and artificial intelligence, with particular emphasis on their applications across diverse scientific and engineering fields. We welcome both methodological developments and application-oriented studies involving the acquisition, processing, reconstruction, analysis, interpretation, and intelligent utilization of signals, images, and multidimensional data.

The scope of this Special Issue is intentionally broad and includes, but is not limited to, digital signal processing, time-frequency analysis, image and video processing, computational imaging, signal reconstruction and enhancement, feature extraction, pattern recognition, machine learning, deep learning, multimodal information fusion, intelligent sensing, and data-driven modeling.

Applications may cover radar and millimeter-wave sensing, remote sensing, communications, biomedical engineering, medical imaging, biological analysis, chemical sensing, environmental monitoring, industrial inspection, intelligent manufacturing, transportation, autonomous systems, robotics, agriculture, energy systems, structural monitoring, Internet of Things, human–machine interaction, and other emerging interdisciplinary areas. Studies that transfer signal processing, image processing, or artificial intelligence methodologies across different domains are particularly encouraged.

The Special Issue seeks to promote the development and cross-domain application of advanced signal and information processing technologies, and to provide a forum connecting fundamental algorithms, intelligent methods, sensing systems, and real-world applications.

Topics of interest for publication include, but are not limited to:

- Millimeter-wave radar system design and optimization;

- Signal processing, time-frequency analysis and signal enhancement;

- Array signal processing, MIMO radar technology and computational imaging;

- Radar target detection, recognition, localization and tracking;

- Deep learning, machine learning and multimodal fusion;

- Intelligent perception algorithms;

- Cross-domain applications of radar sensing in industry, transportation and remote sensing;

- Biomedical sensing, environmental monitoring and intelligent detection.

Dr. Kaitai Guo
Dr. Xiaoguang Yuan
Dr. Jing Liu
Guest Editors

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• digital signal processing
• signal and image processing
• intelligent sensing
• artificial intelligence
• machine learning
• data-driven modeling
• radar and millimeter-wave sensing
• biomedical signal processing
• biological signal processing
• chemical signal processing and sensing
• multimodal data fusion
• cross-domain applications