SAR Imaging and Deep Learning for Sea Target Detection and Maritime Surveillance
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".
Deadline for manuscript submissions: 14 November 2025 | Viewed by 262
Special Issue Editors
Interests: Remote sensing; maritime target detection; deep learning
Interests: signal and image processing; pattern recognition; remote sensing; information fusion
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the rapid development of marine economic and related activities, maritime target detection and surveillance has become a core requirement for safeguarding marine security, maintaining ecological balance, and promoting resource development. Synthetic Aperture Radar (SAR), with its all-weather, all-day, high-resolution imaging capability, has shown irreplaceable advantages in complex marine environments. However, traditional SAR target detection methods are limited by the limitations of artificial feature design, and it is difficult to cope with the problems of target multi-scale changes, motion behavior, complex background interference, etc. In recent years, breakthroughs in deep learning technology have injected new momentum into SAR image interpretation, significantly improving the detection accuracy and adaptability of maritime targets through treatments such as multi-dimensional domain feature fusion, rotational invariance modeling, and real-time detection architecture optimization. The research in this cross-cutting field not only promotes the intelligent transformation of remote sensing technology but also has far-reaching scientific significance and application value for marine situational awareness, disaster emergency response, and marine safety and security.
This Special Issue aims to report the state of the art on the deep integration of SAR imaging technology and deep learning, which fits the direction of Remote Sensing's focus on cutting-edge technological innovation and interdisciplinary applications, such as SAR imaging mechanism optimization, deep learning model innovation, and multimodal data synergy.
The potential themes include, but are not limited to, the following:
- SAR imaging and signal processing in marine environments;
- Electromagnetic scattering modeling in marine environments;
- Maritime target detection;
- Deep learning models and algorithms;
- Marine situational awareness;
- Multi-source data fusion;
- Performance evaluation criteria of detection algorithms in complex scenarios.
Dr. Ding Nie
Prof. Dr. Vassilis Anastassopoulos
Guest Editors
Dr. Hui Chen
Guest Editor Assistant
Manuscript Submission Information
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Keywords
- SAR imaging
- maritime target detection
- deep learning
- electromagnetic scattering
- multi-source data fusion
- marine situational awareness
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