International Journal of Antennas and Propagation
Volume 2016 (2016), Article ID 1671687, 12 pages
http://dx.doi.org/10.1155/2016/1671687
Research Article
FPGA Implementation of Real-Time Compressive Sensing with Partial Fourier Dictionary
National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
Received 18 July 2015; Accepted 13 December 2015
Academic Editor: Atsushi Mase
Copyright © 2016 Yinghui Quan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Linked References
- E. J. Candès, J. Romberg, and T. Tao, “Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information,” IEEE Transactions on Information Theory, vol. 52, no. 2, pp. 489–509, 2006. View at Publisher · View at Google Scholar · View at Scopus
- E. J. Candes and T. Tao, “Near-optimal signal recovery from random projections: universal encoding strategies?” IEEE Transactions on Information Theory, vol. 52, no. 12, pp. 5406–5425, 2006. View at Publisher · View at Google Scholar · View at Scopus
- D. L. Donoho, “Compressed sensing,” IEEE Transactions on Information Theory, vol. 52, no. 4, pp. 5406–5425, 2006. View at Publisher · View at Google Scholar · View at Scopus
- L. Zhang, Z.-J. Qiao, M.-D. Xing, J.-L. Sheng, R. Guo, and Z. Bao, “High-resolution ISAR imaging by exploiting sparse apertures,” IEEE Transactions on Antennas and Propagation, vol. 60, no. 2, pp. 997–1008, 2012. View at Publisher · View at Google Scholar · View at Scopus
- W. Zhang, M. G. Amin, F. Ahmad, A. Hoorfar, and G. E. Smith, “Ultrawideband impulse radar through-the-wall imaging with compressive sensing,” International Journal of Antennas and Propagation, vol. 2012, Article ID 251497, 11 pages, 2012. View at Publisher · View at Google Scholar · View at Scopus
- E. J. Candes and M. B. Wakin, “An introduction to compressive sampling: a sensing/sampling paradigm that goes against the common knowledge in data acquisition,” IEEE Signal Processing Magazine, vol. 25, no. 2, pp. 21–30, 2008. View at Publisher · View at Google Scholar · View at Scopus
- B. K. Natarajan, “Sparse approximate solutions to linear systems,” SIAM Journal on Computing, vol. 24, no. 2, pp. 227–234, 1995. View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- M. Andrecut, “Fast GPU implementation of sparse signal recovery from random projections,” http://arxiv.org/abs/0809.1833v2.
- A. Borghi, J. Darbon, S. Peyronett, T. Chan, and S. Osher, “A simple compressive sensing algorithm for parallel many-core architectures,” CAM Report 08-64, UCLA, 2008. View at Google Scholar
- D. Yang, G. D. Peterson, and H. Li, “Compressed sensing and cholesky decomposition on FPGAs and GPUs,” Parallel Computing, vol. 38, no. 8, pp. 421–437, 2012. View at Publisher · View at Google Scholar · View at Scopus
- M. Karkooti, J. R. Cavallaro, and C. Dick, “FPGA implementation of matrix inversion using QRD-RLS algorithm,” in Proceedings of the 39th Asilomar Conference on Signals, Systems and Computers, pp. 1625–1629, November 2005. View at Scopus
- S. S. Chen, D. L. Donoho, and M. A. Saunders, “Atomic decomposition by basis pursuit,” SIAM Review, vol. 43, no. 1, pp. 129–159, 2001. View at Publisher · View at Google Scholar · View at Scopus
- S. Kunis and H. Rauhut, “Random sampling of sparse trigonometric polynomials, II. Orthogonal matching pursuit versus basis pursuit,” Foundations of Computational Mathematics, vol. 8, no. 6, pp. 737–763, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- J. A. Tropp and A. C. Gilbert, “Signal recovery from random measurements via orthogonal matching pursuit,” IEEE Transactions on Information Theory, vol. 53, no. 12, pp. 4655–4666, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- O. Storaasli and D. Strenski, “Exploring accelerating science applications with FPGAs,” in Proceedings of the 3rd Annual Reconfigurable Systems Summer Institute (RSSI '07), pp. 1–30, Urbana, Ill, USA, July 2007.
- P. Maechler, P. Greisen, N. Felber, and A. Burg, “Matching pursuit: evaluation and implementation for LTE channel estimation,” in Proceedings of the IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems (ISCAS '10), pp. 589–592, Paris, France, May-June 2010. View at Publisher · View at Google Scholar · View at Scopus
- P. Maechler, P. Greisen, B. Sporrer, S. Steiner, N. Felber, and A. Burg, “Implementation of greedy algorithms for LTE sparse channel estimation,” in Proceedings of the 44th Asilomar Conference on Signals, Systems and Computers, pp. 400–405, IEEE, Pacific Grove, Calif, USA, November 2010. View at Publisher · View at Google Scholar · View at Scopus
- A. Septimus and R. Steinberg, “Compressive sampling hardware reconstruction,,” in Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS '10), pp. 3316–3319, Paris, France, May-June 2010. View at Publisher · View at Google Scholar
- M. Mishali, R. Hilgendorf, E. Shoshan, I. Rivkin, and Y. C. Eldar, “Generic sensing hardware and real-time reconstruction for structured analog signals,” in Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS '11), pp. 1748–1751, IEEE, Rio de Janeiro, Brazil, May 2011. View at Publisher · View at Google Scholar
- J. L. V. M. Stanislaus and T. Mohsenin, “High performance compressive sensing reconstruction hardware with QRD process,” in Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS '12), pp. 29–32, Seoul, Republic of Korea, May 2012. View at Publisher · View at Google Scholar · View at Scopus
- P. Maechler, C. Studer, D. E. Bellasi et al., “VLSI design of approximate message passing for signal restoration and compressive sensing,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 2, no. 3, pp. 579–590, 2012. View at Publisher · View at Google Scholar · View at Scopus
- L. Bai, P. Maechler, M. Muehlberghuber, and H. Kaeslin, “High-speed compressed sensing reconstruction on FPGA using OMP and AMP,” in Proceedings of the 19th IEEE International Conference on Electronics, Circuits, and Systems (ICECS '12), pp. 53–56, IEEE, Seville, Spain, December 2012. View at Publisher · View at Google Scholar · View at Scopus
- J. L. V. M. Stanislaus and T. Mohsenin, “Low-complexity FPGA implementation of compressive sensing reconstruction,” in Proceedings of the International Conference on Computing, Networking and Communications (ICNC '13), pp. 671–675, San Diego, Calif, USA, January 2013. View at Publisher · View at Google Scholar · View at Scopus
- F. B. Ren, R. Dorrace, W. Y. Xu, and D. Marković, “A single-precision compressive sensing signal reconstruction engine on FPGAs,” in Proceedings of the 23rd International Conference on Field Programmable Logic and Applications (FPL '13), pp. 1–4, IEEE, Porto, Portugal, September 2013. View at Publisher · View at Google Scholar
- L. Zhang, M. D. Xing, C.-W. Qiu, J. Li, and Z. Bao, “Achieving higher resolution ISAR imaging with limited pulses via compressed sampling,” IEEE Geoscience and Remote Sensing Letters, vol. 6, no. 3, pp. 567–571, 2009. View at Publisher · View at Google Scholar · View at Scopus
- L. Zhang, M. D. Xing, C. W. Qiu, J. L. Sheng, Y. C. Li, and Z. Bao, “Resolution enhancement for inverse synthetic aperture radar imaging under low SNR via improved compressive sensing,” IEEE Transactions on Geoscience and Remote Sensing, vol. 48, no. 10, pp. 3824–3838, 2010. View at Publisher · View at Google Scholar
- H. X. Wang, Y. H. Quan, M. D. Xing, and S. H. Zhang, “ISAR imaging via sparse probing frequencies,” IEEE Geoscience and Remote Sensing Letters, vol. 8, no. 3, pp. 451–455, 2011. View at Publisher · View at Google Scholar · View at Scopus
- S. Shah, Y. Yu, and A. Petropulu, “Step-frequency radar with compressive sampling (SFR-CS),” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '10), pp. 1686–1689, IEEE, Dallas, Tex, USA, March 2010. View at Publisher · View at Google Scholar · View at Scopus
- L. Zhang, Z.-J. Qiao, M. D. Xing, Y. C. Li, and Z. Bao, “High-resolution ISAR imaging with sparse stepped-frequency waveforms,” IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 11, pp. 4630–4651, 2011. View at Publisher · View at Google Scholar · View at Scopus
- A. C. Gurbuz, J. H. McClellan, and W. R. Scott Jr., “Compressive sensing for subsurface imaging using ground penetrating radar,” Signal Processing, vol. 89, no. 10, pp. 1959–1972, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
- A. C. Gurbuz, J. H. McClellan, and W. R. Scott, “A compressive sensing data acquisition and imaging method for stepped frequency GPRs,” IEEE Transactions on Signal Processing, vol. 57, no. 7, pp. 2640–2650, 2009. View at Publisher · View at Google Scholar · View at Scopus
- Y. S. Yoon and M. G. Amin, “Compressed sensing technique for high-resolution radar imaging,” in Signal Processing, Sensor Fusion, and Target Recognition XVII, vol. 6968 of Proceedings of SPIE, Orlando, Fla, USA, March 2008. View at Publisher · View at Google Scholar
- L. C. Potter, E. Ertin, J. T. Parker, and M. Çetin, “Sparsity and compressed sensing in radar imaging,” Proceedings of the IEEE, vol. 98, no. 6, Article ID 5420035, pp. 1006–1020, 2010. View at Publisher · View at Google Scholar · View at Scopus
- Q. Huang, L. Qu, B. Wu, and G. Fang, “UWB through-wall imaging based on compressive sensing,” IEEE Transactions on Geoscience and Remote Sensing, vol. 48, no. 3, pp. 1408–1415, 2010. View at Publisher · View at Google Scholar · View at Scopus
- Y. H. Quan, L. Zhang, M. D. Xing, and Z. Bao, “Velocity ambiguity resolving for moving target indication by compressed sensing,” Electronics Letters, vol. 47, no. 22, pp. 1249–1251, 2011. View at Publisher · View at Google Scholar · View at Scopus
- Y. Quan, L. Zhang, Y. Li, H. Wang, and M. Xing, “OTHR spectrum reconstruction of maneuvering target with compressive sensing,” International Journal of Antennas and Propagation, vol. 2014, Article ID 870352, 10 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
- F. B. Ren, R. Dorrace, W. Y. Xu, and D. Marković, “A single-precision compressive sensing signal reconstruction engine on FPGAs,” in Proceedings of the 23rd International Conference on Field Programmable Logic and Applications (FPL '13), pp. 1–4, IEEE, Porto, Portugal, September 2013. View at Publisher · View at Google Scholar · View at Scopus
- C. K. Singh, S. H. Prasad, and P. T. Balsara, “VLSI architecture for matrix inversion using modified Gram-Schmidt based QR decomposition,” in Proceedings of the 20th International Conference on VLSI Design. Held Jointly with 6th International Conference on Embedded Systems, pp. 836–841, IEEE, Bangalore, India, January 2007. View at Publisher · View at Google Scholar
- Y. Fang, L. Chen, J. Wu, and B. Huang, “GPU implementation of orthogonal matching pursuit for compressive sensing,” in Proceedings of the 17th IEEE International Conference on Parallel and Distributed Systems (ICPADS '11), pp. 1044–1047, IEEE, Tainan, Taiwan, December 2011. View at Publisher · View at Google Scholar · View at Scopus
- P. Blache, H. Rabah, and A. Amira, “High level prototyping and FPGA implementation of the orthogonal matching pursuit algorithm,” in Proceedings of the 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA '12), pp. 1336–1340, IEEE, Montreal, Canada, July 2012. View at Publisher · View at Google Scholar