An Improved Target Searching and Imaging Method for CSAR

NEURAL INFORMATION PROCESSING, ICONIP 2023, PT III(2024)

引用 0|浏览1
暂无评分
摘要
Circular Synthetic Aperture Radar (CSAR) has attracted much attention in the field of high-resolution SAR imaging. In order to shorten the computation time and improve the imaging effect, in this paper, we propose a fast CSAR imaging strategy that searches the target and automatically selects the area of interest for imaging. The first step is to find the target and select the imaging center and interest imaging area based on the target search algorithm, the second step is to divide the full-aperture data into sub-apertures according to the angle, the third step is to approximate the sub-apertures as linear arrays and imaging them separately, and the last step is to perform sub-image fusion to obtain the final CSAR image. This method can greatly reduce the imaging time and obtain well-focused CSAR images. The proposed algorithm is verified by both simulation and processing real data collected with our mmWave imager prototype utilizing commercially available 77-GHz MIMO radar sensors. Through the experimental results we verified the performance and the superiority of the our algorithm.
更多
查看译文
关键词
Circular Synthetic Aperture Radar,Sub-Apertures Divide,2D-Multiple Signal Classification
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要