Development of Raw Data Processing System for CP-SAR On-board JX-2 UAV using Mobile Heterogeneous Computing

Bambang Setiadi, Good Fried Panggabean, Josaphat Tetuko Sri Sumantyo, Koo Voon Chet

Abstract


This paper presents the development of unmanned aerial vehicle (UAV) -based Circularly Polarized Synthetic Aperture Radar (CP-SAR) raw data processing system for the experimental JX-2 UAV. First, we present the design and outline of CP-SAR system, followed by derivation of resolution and raw data rate value from axial ratio and geometry. Following the signal processing requirements, we propose to use mobile heterogeneous platform for on-board raw SAR data processing system. Then we describe the raw data processing steps based on Range-Doppler Algorithm for stripmap mode UAV SAR. Experiment results using a middle-end CPU-GPU mobile heterogeneous hardware development kit with CUDA programming interface and raw data input from actual UAV mission demonstrate the capability of the proposed mobile heterogeneous platform for SAR processing on-board JX-2 UAV.

Keywords


synthetic aperture radar, SAR processing, Range-Doppler, Mobile Heterogeneous Computing, CPU, Graphic Processing Units, GPU, Common Unified Device Architecture

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References


M. Skolnik, Radar Handbook, Third Edition, Third. McGraw-Hill Professional, 2008.

A. Moreira, P. Prats-iraola, M. Younis, G. Krieger, I. Hajnsek, and K. P. Papathanassiou, “A tutorial on synthetic aperture radar,” IEEE Geosci. Remote Sens. Mag., vol. 1, no. 1, pp. 6–43, 2013.

J. T. Sri Sumantyo, “Circularly Polarized Synthetic Aperture Radar Onboard Unmanned Aerial Vehicle (CP-SAR UAV),” in Autonomous Control Systems and Vehicles, K. Nonami, M. Kartidjo, K.-J. Yoon, and A. Budiyono, Eds. Springer Japan, 2013, pp. 175–192.

V. C. Koo, Y. K. Chan, V. Gobi, M. Y. Chua, C. H. Lim, C.-S. Lim, C. C. Thum, T. S. Lim, Z. bin Ahmad, K. A. Mahmood, M. H. Bin Shahid, C. Y. Ang, W. Q. Tan, P. N. Tan, K. S. Yee, W. G. Cheaw, H. S. Boey, A. L. Choo, and B. C. Sew, “A New Unmanned Aerial Vehicle Synthetic Aperture Radar For Environmental Monitoring,” Prog. Electromagn. Res., vol. 122, pp. 245–268, 2012.

M. Edrich, “Ultra-lightweight synthetic aperture radar based on a 35 GHz FMCW sensor concept and online raw data transmission,” IEE Proc. - Radar, Sonar Navig., vol. 153, no. 2, p. 129, 2006.

K. Y. Chan and V. C. Koo, “AN INTRODUCTION TO SYNTHETIC APERTURE RADAR (SAR),” Prog. Electromagn. Res. B, vol. 2, pp. 27–60, 2008.

P. G. Meisl, M. R. Ito, and I. G. Cumming, “Parallel processors for synthetic aperture radar imaging,” in Proceedings of the 1996 ICPP Workshop on Challenges for Parallel Processing, 1996, pp. 124–131.

I. G. Cumming and J. R. Bennett, “Digital processing of Seasat SAR data,” Acoust. Speech, Signal Process. IEEE Int. Conf. ICASSP ’79., pp. 710–718, 1979.

C. Clemente and J. J. Soraghan, “Range Doppler and chirp scaling processing of synthetic aperture radar data using the fractional Fourier transform,” IET Signal Process., vol. 6, no. 5, p. 503, 2012.

M. di Bisceglie, M. Di Santo, C. Galdi, R. Lanari, and N. Ranaldo, “Synthetic Aperture Radar Processing with GPGPU,” IEEE Signal Process. Mag., vol. 27, no. 2, pp. 69–78, Mar. 2010.

I. G. Cumming and F. H. Wong, Digital Signal Processing of Synthetic Aperture Radar Data: Algorithms and Implementation (Artech House Remote Sensing Library). Artech House, 2004.

Y. C. Lee, V. C. Koo, and Y. K. Chan, “FPGA-based Pre-processing Unit for Real-time Synthetic Aperture Radar ( SAR ) Imaging,” in Progress In Electromagnetics Research Symposium, 2012, pp. 1087–1091.

G. F. Panggabean, B. Setiadi, and J. T. S. Sumantyo, “A Single-on-Chip for Onboard SAR Imaging Processor Based on the LEON3,” in The 11th International Conference on Intelligent Unmanned Systems, 2015.

A. W. Doerry and D. F. Dubbert, “Digital signal processing applications in high-performance synthetic aperture radar processing,” in Signals, Systems and Computers, 2003. Conference Record of the Thirty-Seventh Asilomar Conference on, 2003, vol. 1, pp. 947–949 Vol.1.

Z. Sanaei, S. Abolfazli, A. Gani, and R. Buyya, “Heterogeneity in mobile cloud computing: Taxonomy and open challenges,” IEEE Commun. Surv. Tutorials, vol. 16, no. 1, pp. 369–392, 2014.

P. Li, X. Wang, D. Zhang, and C. Deng, “The Design of Miniature UHF SAR Antenna,” in 2006 CIE International Conference on Radar, 2006, pp. 1–2.

Z. Fang and J. Xia, “A miniature implementation of air-born SAR real-time processing,” in 2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar, 2009, pp. 939–942.

S. I. Tsunoda, F. Pace, J. Stence, M. Woodring, W. H. Hensley, A. W. Doerry, and B. C. Walker, “Lynx: a high-resolution synthetic aperture radar,” in 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484), 2000, vol. 5, pp. 51–58.

A. W. Doerry and D. F. Dubbert, “Digital signal processing applications in high-performance synthetic aperture radar processing,” in The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, 2003, vol. 1, pp. 947–949.

Y.-C. Wang and K.-T. Cheng, “Energy and Performance Characterization of Mobile Heterogeneous Computing,” in 2012 IEEE Workshop on Signal Processing Systems, 2012, pp. 312–317.

M. Edwards, D. Madsen, C. Stringham, A. Margulis, B. Wicks, and D. G. Long, “microASAR: A Small, Robust LFM-CW SAR for Operation on UAVs and Small Aircraft,” in IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008, vol. 5, pp. V – 514–V – 517.

C. Stringham and D. G. Long, “Improved processing of the casie SAR data,” in 2011 IEEE International Geoscience and Remote Sensing Symposium, 2011, pp. 1389–1392.

Y. Yohandri, V. Wissan, I. Firmansyah, J. . Sri Sumantyo, H. Kuze, P. Rizki Akbar, and J. T. Sri Sumantyo, “Development of Circularly Polarized Array Antenna for Synthetic Aperture Radar Sensor Installed on UAV,” Prog. Electromagn. Res. C, vol. 19, no. January, pp. 119–133, 2011.

K. Suto, J. T. Sri Sumantyo, C. W. Guey, and K. V. Chet, “FPGA Based Multiple Preset Chirp Pulse Generator For Synthetic Aperture Radar Onboard Unmanned Aerial Vehicle System,” in The 20th CEReS International Symposium, Symposium on Microsatellite for Remote Sensing 2013, 2013, pp. 2–3.

W. L. Stutzman, Polarization in electromagnetic systems. Artech House, 1993.

P. R. R. Akbar, J. T. T. Sri Sumantyo, V. C. C. Koo, and H. Kuze, “Estimation of Data Memory Capacity for Circularly Polarized Synthetic Aperture Radar Onboard Unmanned Aerial Vehicle (CPSAR-UAV),” J. Remote Sens. Earth Sci., vol. 7, pp. 24–35, 2011.

F. M. Henderson, Principles and Applications of Imaging Radar (Manual of Remote Sensing, Volume 2). Wiley, 1998.

P. Rizki Akbar, J. Tetuko S. S., and H. Kuze, “A novel circularly polarized synthetic aperture radar (CP-SAR) system onboard a spaceborne platform,” Int. J. Remote Sens., vol. 31, no. 4, pp. 1053–1060, Apr. 2010.

J. Bennett and I. Cumming, “A Digital Processor for the Production of Seasat Synthetic Aperture Radar Imagery,” LARS Symp., 1979.

R. Kumar, D. M. Tullsen, N. P. Jouppi, and P. Ranganathan, “Heterogeneous chip multiprocessors,” Computer (Long. Beach. Calif)., vol. 38, no. 11, pp. 32–38, Nov. 2005.

V. Petrucci, O. Loques, D. Mossé, R. Melhem, N. A. Gazala, and S. Gobriel, “Energy-Efficient Thread Assignment Optimization for Heterogeneous Multicore Systems,” ACM Trans. Embed. Comput. Syst., vol. 14, no. 1, pp. 1–26, 2015.

M. A. Watkins and D. H. Albonesi, “ReMAP: A reconfigurable heterogeneous multicore architecture,” in Proceedings of the Annual International Symposium on Microarchitecture, MICRO, 2010, pp. 497–508.

Z. Zhong, V. Rychkov, and A. Lastovetsky, “Data Partitioning on Heterogeneous Multicore Platforms,” 2011 IEEE Int. Conf. Clust. Comput., pp. 580–584, 2011.

Y.-C. Wang and K.-T. (Tim) Cheng, “Energy and Performance Characterization of Mobile Heterogeneous Computing,” 2012 IEEE Work. Signal Process. Syst., pp. 312–317, 2012.

NVIDIA, “Data Sheet NVIDIA Tegra K1 Series Processors with Kepler Mobile GPU for Embedded Applications,” 2015.

J. Malcolm, P. Yalamanchili, C. McClanahan, V. Venugopalakrishnan, K. Patel, and J. Melonakos, “ArrayFire: a GPU acceleration platform,” in Proc. SPIE 8403, Modeling and Simulation for Defense Systems and Applications VII, 2012, p. 84030A–84030A–8.


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