Artificial Intelligence(AI)-Assisted Synthetic Aperture Radar (SAR) Data Processing and Application

Dear Colleagues,

Synthetic aperture radar (SAR) sensors are widely used in remote sensing applications for their all-day and all-weather imaging abilities. With the continuous emergence of new technologies, such as polarimetric SAR (PolSAR), interferometric SAR (InSAR), differential interferometric SAR (DInSAR), permanent scatterers SAR interferometry (PSInSAR), tomography SAR (TomoSAR), etc., the SAR opens a new window for us to understand the world, and its application has been extended to various fields, such as object monitoring, environmental protection, disaster management, urban planning, situational awareness, etc.

The massive amount of data obtained via a large number of satellites or aerial vehicles poses opportunities and challenges for the processing and application of SAR remote sensing data. How to interpret and utilize these data efficaciously and efficiently is a hot and difficult research topic in the related communities. In recent years, artificial intelligence (AI), especially deep learning (DL) techniques, has provided promising tools to overcome many challenging issues in the processing and utilizing of SAR data.

In this Special Issue, we are looking forward to receiving a variety of research contributions, whether they are theoretical or heuristic, that focus on the processing and/or utilizing of SAR data/images with AI techniques. We expect that new research will address practical problems with the help of advanced AI methods, and provide valuable insights into developing better SAR data processing techniques for a broad range of applications.

Original submissions are welcome. Suggested themes of interest include, but are not limited to, the following:

SAR Data Processing:

• Advances in SAR data pre-processing, processing, or post-processing technologies.
• Advances in InSAR, DInSAR, PSInSAR, TomoSAR technologies.
• SAR image enhancement, augmentation, or generation.
• Image fusion or translation between SAR and optical sensors.

SAR Data Applications:

• Advances in SAR data/image based object detection, recognition, re-identification, classification, and tracking.
• SAR data/image based urban, land, ocean, ice, soil, and vegetation applications.

Prof. Dr. Haitao Lang
Prof. Dr. Hyung-Sup Jung
Prof. Dr. Xudong Lai
Guest Editors

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• synthetic aperture radar (SAR)
• remote sensing
• data processing
• deep learning (DL)
• artificial intelligence (AI)