High-Precision Calibration and Polarimetric and Interferometric Image Processing Technology
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 815
Special Issue Editors
Interests: SAR calibration technology; PolSAR and PolInSAR processing and applications; target detection and identification algorithms
Interests: radar and optical remote sensing; microwave scattering models of rice/forest; applications of SAR polarimetry and polarimetric interferometry for agriculture and forestry
Special Issue Information
Dear Colleagues,
Synthetic aperture radar (SAR) plays a vital role in Earth observation. With the launch of new spaceborne SAR missions, SAR data have become increasingly diverse in terms of frequency bands (L/S/C/X/Ku), polarimetric modes (dual, full, and compact polarization), imaging modes (Stripmap, Spotlight, ScanSAR, and TopSAR), satellite orbits (GEO, MEO, LEO), and constellation configurations (single-satellite, dual-satellite, and large-scale multi-satellite constellations). On the other hand, miniaturized and lightweight airborne SAR systems, such as UAV SAR, have become an important technological trend. This diversity brings both challenges and opportunities for developing high-precision calibration and advanced processing techniques to support quantitative SAR data applications. Calibration is the basis of quantitative SAR applications. High-precision calibration methods are essential for ensuring geometric, radiometric, polarimetric, and interferometric accuracy, enabling the generation of high-quality, multi-dimensional SAR datasets. SAR data are also susceptible to various distortions caused by environmental, instrumental, and system-related factors, making SAR data processing increasingly complex. Therefore, it is vital to develop dedicated processing algorithms to estimate and mitigate these distortions. Novel processing techniques are urgently needed to enhance the quality of high-resolution SAR, polarimetric SAR, and polarimetric interferometric SAR data, thereby advancing their quantitative applications in diverse remote sensing scenarios.
This Special Issue will bring together high-quality contributions that focus on recent advances in the “High-Precision Calibration and Polarimetric and Interferometric Image Processing Technology”. Both original research articles with innovative ideas and review articles discussing state-of-the-art research are welcome.
We would like to invite high-quality research papers on the following topics:
- Novel in-orbit processing techniques: Edge computing and real-time processing, intelligent in-orbit processing, lightweight neural networks for in-orbit processing, and MGC/AGC;
- Calibration methods and techniques: Radiometric, polarimetric, and interferometric calibration; cross-calibration; in-orbit calibration; automatic calibration for large satellite constellations; long-term calibration; and satellite health monitoring;
- SAR data validation approaches: Systematic error analysis and modeling and AI-based intelligent assessment techniques;
- Pre-processing and correction techniques: Terrain correction, speckle noise filtering, Faraday rotation compensation, atmospheric delay correction, and super-resolution reconstruction;
- UAV-SAR data processing: UAV attitude compensation, high-precision calibration, real-time processing, and intelligent processing;
- Multi-source data processing: High-precision image matching, geolocation, multi-baseline InSAR, PolInSAR, TomoSAR, and multi-dimensional data fusion and applications using both physical modeling and deep learning techniques.
Dr. Fengli Zhang
Dr. Kun Li
Prof. Dr. Chang Liu
Guest Editors
Manuscript Submission Information
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Keywords
- novel calibration algorithms
- polarimetric and interferometric calibration models
- application of big data and artificial intelligence for SAR calibration
- calibration strategies for ongoing and upcoming SAR missions
- multi-source data processing with physical modeling and deep learning techniques
- quantitative applications of calibrated SAR data
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