SAR-Based Signal Processing and Target Recognition (Second Edition)

Dear Colleagues,

Synthetic aperture radar (SAR) is a class of remote sensors that work during all weather conditions and at all times of day, regardless of whether they are airborne or spaceborne.  Currently, SAR can provide very high-resolution images and multi-dimensional (such as multi-channel, multi-aspect, multi-frequency, multi-polarization, multi-temporal, etc.) data during a limited period of time, enhancing the spatial-time resolution of the observations. Recently, SAR technology has been developing towards multi-dimensional imaging and fine-grained image recognition trends. Meanwhile, the paradigms of SAR imaging and information perceptions have also undergone changes to multi-mode, multi-dimensional, and intelligent processing strategies.

Recently, machine learning and deep learning methods have been applied to SAR imaging and target recognition. Our Special Issue “SAR-Based Signal Processing and Target Recognition (First Edition)” introduced some advanced signal processing and target recognition technologies in SAR, based on learning algorithms. Compared to conventional model-based approaches, the learning algorithms that benefit from the advanced processing framework and SAR data are more adaptive and show superior performance. However, when limited to small data sets, complex scenes, scattering sensitivity variations on the azimuth, etc., these learning algorithms may suffer from bad generalization capability and low robustness.

This Special Issue invites contributions on the latest developments and advances in SAR-based signal processing and target recognition technologies. Topics of interest include (but are not limited to) multi-mode SAR imaging, multi-dimensional SAR imaging, SAR interference and anti-interference, and SAR target detection and recognition:

• Multi-mode/multi-dimensional SAR imaging theory and architecture;
• Three-dimensional SAR/ISAR imaging and parameter inversion;
• Sparse techniques of SAR, ISAR, and tomoSAR imaging;
• Machine learning and deep learning aided SAR/ISAR imaging;
• SAR interference and anti-interference;
• Physical model informed interpretable deep learning for SAR imaging and target recognition;
• SAR/InSAR image enhancement (such as despeckling and phase noise reduction);
• SAR/ISAR image simulation and generation;
• Intelligent detection and recognition for SAR images;
• SAR image interpretation with knowledge guided deep learning;
• PolSAR image classification;
• SAR imaging semantic segmentation and change detection;
• SAR target characterizing;
• Real-time processing system for SAR images;
• Multi-modal remote sensing data (including SAR images) fusion, analysis and understanding.

Prof. Dr. Lan Du
Prof. Dr. Gang Xu
Prof. Dr. Haipeng Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 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.

• SAR imaging
• sparse signal processing
• parameter inversion
• SAR target recognition
• SAR target detection
• deep learning

• SAR-Based Signal Processing and Target Recognition in Remote Sensing (25 articles)