A Novel WasSAR Image Offset Information Estimation Method for 3-D Information Acquisition
The Wide-Angle Stare Synthetic Aperture Radar (WasSAR), as an emerging SAR observation mode, enables long-duration, multi-angular imaging of a scene, demonstrating remarkable advantages in three-dimensional (3D) information acquisition. A critical step in the process of 3D information extraction lies in accurately determining the displacement information between sub-aperture images captured from adjacent azimuth angles. During the WasSAR imaging process, spatial targets exhibit positional discrepancies in imaging results obtained from different azimuth perspectives, making pixel-wise displacement estimation in SAR images highly challenging, especially in complex scenarios. To address this challenge, this study proposes an innovative displacement estimation method for WasSAR imagery tailored for 3D information extraction. The proposed approach begins with brightness equalization preprocessing to harmonize the brightness distribution between two images, ensuring the accuracy of subsequent processing steps. This is followed by an initial estimation using block-based registration techniques based on the Enhanced Correlation Coefficient (ECC). Finally, an improved optical flow algorithm is employed to achieve precise displacement estimation, significantly enhancing the accuracy and reliability of displacement information estimation between SAR images. A series of experiments were conducted using Ku-band Mountain scene datasets acquired by the National University of Defense Technology. The experimental results include a comprehensive comparative analysis with several existing displacement estimation methods, showcasing the superior performance of the proposed algorithm across multiple key performance metrics. The proposed algorithm’s performance in 3D information extraction applications was also evaluated, confirming its effectiveness and high practicality.
Authors
- Leping Chen (ORCID: https://orcid.org/0000-0002-2742-0326)
- Daoxiang An (ORCID: https://orcid.org/0000-0002-1363-9140)
- Yishi Li (ORCID: https://orcid.org/0000-0002-7284-5067)
- Yongping Song (ORCID: https://orcid.org/0000-0003-4191-0548)
- Xiaotao Huang
Institutions
- National University of Defense Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tgrs.2025.3528463
- Citations
- 1
- Primary Topic
- Optical Systems and Laser Technology
- Type
- article
- Field-Weighted Citation Impact
- 0.73
Funders
- National Natural Science Foundation of China