Hybrid Optoelectronic SAR Moving Target Detection and Imaging Method
In this study, a hybrid optoelectronic synthetic aperture radar (SAR) moving target detection and imaging (OCMTI) method is introduced to address the challenges faced when processing large volumes of SAR data while focusing on key moving targets. Traditional algorithms often demand substantial computational resources, with the Fourier transform representing a widely implemented yet computationally intensive operation (typically O(N2) or O(NlogN) complexity). In contrast, optical systems can perform Fourier transforms inherently at the speed of light. The OCMTI method leverages this advantage and integrates optical and electronic processing to enable the rapid detection and selective imaging of moving targets. First, imaging parameters are dynamically configured based on the velocity range of the moving targets of interest and multiple coarse images of the entire scene are generated using an optical system. These images are then processed using a computer-aided detection system to identify candidate targets, and each target is subjected to fine imaging and parameter estimation. The refined images of detected targets are finally integrated into a single image with a suppressed background. The OCMTI method can rapidly detect moving targets, and the time complexity of moving target detection is proportional to the number of image pixels. The correct detection rate for a single image can reach 97%. The efficiency of this method in detecting and imaging moving targets is experimentally validated, which reveals it as a promising solution for time-sensitive applications. The OCMTI method bridges optical speed with electronic flexibility, thereby advancing SAR systems toward real-time, target-oriented operations.
Authors
- Kaizhi Wang (ORCID: https://orcid.org/0000-0002-5485-2685)
- Duo Wang (ORCID: https://orcid.org/0000-0002-2923-8771)
- Jiajia Chen (ORCID: https://orcid.org/0000-0001-9754-6509)
- Enhua Zhang
Institutions
- Shanghai Jiao Tong University (CN)
- Yiwu Science and Technology Research Institute (CN)
Publication Details
- Journal
- Remote Sensing
- Published
- 2025-09-02
- DOI
- https://doi.org/10.3390/rs17173057
- Primary Topic
- Advanced SAR Imaging Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China