Target Detection and Classification Based on SAR

Dear Colleagues,

Synthetic Aperture Radar (SAR) is one of the most-used tools since it allows all-day and almost all-weather observations with a moderate-to-fine spatial resolution. At its current stage, SAR has the capability to provide very high-resolution images and multi-dimensional (such as multi-channel, multi-aspect, multi-frequency, multi-polarization, multi-temporal, etc.) data, enhancing the spatial-time details of the observations. With the development of machine learning and deep learning methods, the ability to detect and identify target types from SAR data has been greatly improved. However, there is still room to improve both models and methods. The goal of this special issue is to gather high-quality and original contributions that reach beyond the conventional ideas and approaches, and the topics of interest include, but not limited to:

• Time-sensitivity target detection and identification;
• Terrain classification and applications;
• Change detection for classifying man-made targets and nature targets;
• Synergies between satellite sensors with airborne platforms and multiple satellite SAR;
• The use of multi-dimensional information to interpret and quantitatively evaluate the target recognition capability;
• Use of machine learning and the build-up of annotated training databases;
• Artificial Intelligence for SAR image processing.

Prof. Dr. Gui Gao
Dr. Xi Zhang 
Dr. Dingfeng Duan
Guest Editors

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