Parallel Processing of SAR Imaging Algorithms for Large Areas Using Multi-GPU

  • Xue WangEmail author
  • Jiabin Yuan
  • Xingfang Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9483)


The procedure of Synthetic Aperture Radar (SAR) data processing is extraordinarily time-consuming. The traditional processing modes are hard to satisfy the demand for real-time which are based on CPU. There have been some implementations on singe GPU owing to its excellent ability of parallel processing. But there is no implementation on multi-GPU for larger areas. A multi-GPU parallel processing method is proposed including task partitioning and communication hiding in this paper. Furthermore, a detailed comparison of implementation effect among Range Doppler algorithm (RDA), Chirp Scaling algorithm (CSA) and \( \omega K \) algorithm (\( \omega KA \)) has been shown in this paper by implementing them on multi-GPU. Experimental results show \( \omega KA \) has the longest execution time and the highest speedup compared to RDA and CSA. All the algorithms satisfy real-time demand on multi-GPU. Researches can select the most suitable algorithm according to our conclusions. The parallel method can be extended to more GPU and GPU clusters.


SAR imaging Multi-GPU Parallelization RDA CSA \( \omega KA \) 


  1. 1.
    Soumekh, M.: Moving target detection in foliage using along track monopulse synthetic aperture radar imaging. IEEE Trans. Image Process. 6(8), 1148–1163 (1997)CrossRefGoogle Scholar
  2. 2.
    Koskinen, J.T., Pulliainen, J.T., Hallikainen, M.T.: The use of ERS-1 SAR data in snow melt monitoring. IEEE Trans. Geosci. Remote Sens. 35(3), 60–610 (1997)CrossRefGoogle Scholar
  3. 3.
    Sharma, R., Kumar, S.B., Desai, N.M., Gujraty, V.R.: SAR for disaster management. IEEE Aerosp. Electron. Syst. Mag. 23(6), 4–9 (2008)CrossRefGoogle Scholar
  4. 4.
    Liang, C., Teng, L.: Spaceborne SAR real-time quick-look system. Trans. Beijing Inst. Technol. 6, 017 (2008)Google Scholar
  5. 5.
    Tang, Y.S., Zhang, C.Y.: Multi-DSPs and SAR real-time signal processing system based on cPCI bus. In: 2007 1st Asia and Pacific Conference on Synthetic Aperture Radar, pp. 661–663. IEEE (2007)Google Scholar
  6. 6.
    Xiong, J.J., Wang, Z.S., Yao, J.P.: The FPGA design of on board SAR real time imaging processor. Chin. J. Electron. 33(6), 1070–1072 (2005)Google Scholar
  7. 7.
    Marchese, L., Doucet, M., Harnisch, B., Suess, M., Bourqui, P., Legros, M., Bergeron, A.: Real-time optical processor prototype for remote SAR applications. In: Proceedings of SPIE7477, Image and Signal Processing for Remote Sensing XV, pp. 74771H–74771H (2009)Google Scholar
  8. 8.
    Cumming, I.G., Wong, F.H.: Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation. Artech House, Norwood (2005)Google Scholar
  9. 9.
    Zhang, S., Chu, Y.L.: GPU High Performance Computing: CUDA. Waterpower Press, Bejing (2009)Google Scholar
  10. 10.
    Meng, D.D., Hu, Y.X., Shi, T., Sun, R.: Airborne SAR real-time imaging algorithm design and implementation with CUDA on NVIDIA GPU. J. Radars 2(4), 481–491 (2013)CrossRefGoogle Scholar
  11. 11.
    Wu, Y.W., Chen, J., Zhang, H.Q.: A real-time SAR imaging system based on CPUGPU heterogeneous platform. In: 11th International Conference on Signal Processing, pp. 461–464. IEEE (2012)Google Scholar
  12. 12.
    Malanowski, M., Krawczyk, G., Samczynski, P., Kulpa, K., Borowiec, K., Gromek, D.: Real-time high-resolution SAR processor using CUDA technology. In: 2013 14th International Radar Symposium (IRS), pp. 673–678. IEEE (2013)Google Scholar
  13. 13.
    Bhaumik Pandya, D., Gajjar, N.: Parallelization of synthetic aperture radar (SAR) imaging algorithms on GPU. Int. J. Comput. Sci. Commun. (IJCSC) 5, 143–146 (2014)Google Scholar
  14. 14.
    Song, M.C., Liu, Y.B., Zhao, F.J., Wang, R., Li, H. Y.: Processing of SAR data based on the heterogeneous architecture of GPU and CPU. In: IET International Radar Conference 2013, pp. 1–5. IET (2013)Google Scholar
  15. 15.
    Ning, X., Yeh C., Zhou, B., Gao, W., Yang, J.: Multiple-GPU accelerated range-doppler algorithm for synthetic aperture radar imaging. In: 2011 IEEE Radar Conference (RADAR), pp. 698–701. IEEE (2011)Google Scholar
  16. 16.
    Tiriticco, D., Fratarcangeli, M., Ferrara, R., Marra, S.: Near-real-time multi-GPU wk algorithm for SAR processing. In: Proceedings of the 2014 Conference on Big Data from Space, pp. 263–266. Publications Office of the European Union (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjingChina

Personalised recommendations