Abstract
The Synthetic Aperture Radar (SAR) system is a kind of modern high-resolution microwave imaging radar used in all-weather and all day long to provide remote sensing means and generate high resolution images of the land under illumination of radar beam. Unlike optical sensors, SAR algorithm needs a post-processing process on the data acquired to form the final image. In this article, we use the General Purpose Graphic Processing Units (GPGPU) to accelerate two of SAR algorithms, PGA (Phase Gradient Autofocus) and PDE (Partial Differential Equations), which are two computational intensive algorithms in the post-processing process for the system. Our work shows that the GPU architecture has different acceleration effects on the two algorithms. PGA can achieve an acceleration of 21.7% and PDE can get a speed up of 2.58\(\times \) on GPGPU. We analyse the reasons for the results and conclude that GPU is a promising platform to accelerate the SAR system.
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Acknowledgments
This work is supported by National Science Foundation of China (Grant No. 61170083, 61373032) and Specialized Research Fund for the Doctoral Program of Higher Education (Grant No. 20114307110001).
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Zhang, Y., Xing, Z., Liu, C., Tang, C., Chen, L., Wang, Q. (2016). Optimization of Two Bottleneck Programs in SAR System on GPGPU. In: Xu, W., Xiao, L., Li, J., Zhang, C., Zhu, Z. (eds) Computer Engineering and Technology. NCCET 2016. Communications in Computer and Information Science, vol 666. Springer, Singapore. https://doi.org/10.1007/978-981-10-3159-5_11
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DOI: https://doi.org/10.1007/978-981-10-3159-5_11
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