2019-06-10
Comparative Study on Sparse and Recovery Algorithms for Antenna Measurement by Compressed Sensing
By
Progress In Electromagnetics Research M, Vol. 81, 149-158, 2019
Abstract
Compressed sensing (CS) is utilized in antenna measurements. The antenna data are compressed using the CS method, and the performances of different sparse and recovery algorithms of CS are used to solve antenna measurements. Experiments are conducted on various types of antennas. The results show that efficiency can be greatly improved by reducing the number of measurement points. The best reconstruction performance is exhibited by the Discrete Wavelet Transform (DWT) algorithm combined with the Compressive Sampling Matching Pursuit (COSAMP) algorithm.
Citation
Liang Zhang, Tianting Wang, Yang Liu, Meng Kong, and Xian-Liang Wu, "Comparative Study on Sparse and Recovery Algorithms for Antenna Measurement by Compressed Sensing," Progress In Electromagnetics Research M, Vol. 81, 149-158, 2019.
doi:10.2528/PIERM19041803
References

1. Duarte, M. F., et al. "Single-pixel imaging via compressive sampling," IEEE Signal Processing Mag., Vol. 25, No. 2, 83-91, 2008.
doi:10.1109/MSP.2007.914730        Google Scholar

2. Lustig, M., D. Donoho, and J. M. Pauly, "Sparse MRI: The application of compressed sensing for rapid MR imaging," Magnetic Resonance in Medicine, Vol. 58, No. 6, 1182-1195, 2007.
doi:10.1002/mrm.21391        Google Scholar

3. Paredes, J. L., G. R. Arce, and Z. Wang, "Ultra-wideband compressed sensing: Channel estimation," IEEE Journal of Selected Topics in Signal Processing, Vol. 1, No. 3, 383-395, 2007.
doi:10.1109/JSTSP.2007.906657        Google Scholar

4. Bajwa, W., et al. "Compressive wireless sensing," International Conference on Information Processing in Sensor Networks ACM, Vol. 402, No. 2, 134-142, 2006.        Google Scholar

5. Chang, J., W. Zhang, S. Zhang, et al. "A novel SAR imaging algorithm based on compressed sensing," IEEE Cie International Conference on Radar, IEEE, 2006.        Google Scholar

6. Lin, X. H., G. Y. Xue, and P. Liu, "Novel data acquisition method for interference suppression in dual-channel SAR," Progress In Electromagnetics Research, Vol. 144, 79-92, 2014.
doi:10.2528/PIER13111207        Google Scholar

7. Migliore, D. M., "A simple introduction to compressed sensing/sparse recovery with applications in antenna measurements," IEEE Antennas and Propagation Magazine, Vol. 56, No. 2, 14-26, 2014.
doi:10.1109/MAP.2014.6837061        Google Scholar

8. Cornelius, R., D. Heberling, N. Koep, et al. "Compressed sensing applied to spherical near-field to far-field transformation," European Conference on Antennas and Propagation, IEEE, 2016.        Google Scholar

9. Fuchs, B., L. L. Coq, S. Rondineau, et al. "Fast antenna far-field characterization via sparse spherical harmonic expansion," IEEE Transactions on Antennas & Propagation, Vol. 65, No. 99, 1, 2017.        Google Scholar

10. Zhang, L., F. Wang, T. Wang, X. Y. Cao, M. S. Chen, and X. L. Wu, "Fast antenna far-field measurement for sparse sampling technology," Progress In Electromagnetics Research M, Vol. 72, 145-152, 2018.
doi:10.2528/PIERM18042509        Google Scholar

11. Donoho, D. L., "Compressed sensing," IEEE Transactions on Information Theory, Vol. 52, No. 4, 1289-1306, 2006.
doi:10.1109/TIT.2006.871582        Google Scholar

12. Donoho, D. L., Y. Tsaig, I. Drori, et al. "Sparse solution of underdetermined systems of linear equations by stagewise orthogonal matching pursuit," IEEE Transactions on Information Theory, Vol. 58, No. 2, 1094-1121, 2012.
doi:10.1109/TIT.2011.2173241        Google Scholar

13. Needell, D. and J. A. Tropp, "CoSaMP: Iterative signal recovery from incomplete and inaccurate samples," Appl. Comput. Harmon. Anal., Vol. 26, No. 3, 301-321, 2008.
doi:10.1016/j.acha.2008.07.002        Google Scholar

14. Chartrand, R. and W. Yin, "Iteratively reweighted algorithms for compressive sensing," IEEE International Conference on Acoustics, Speech and Signal Processing, 2008, ICASSP 2008, IEEE, 2008.        Google Scholar

15. Huggins, P. S. and S. W. Zucker, "Greedy base pursuit," IEEE Transactions on Signal Processing, Vol. 55, No. 7, 3760-3772, 2007.
doi:10.1109/TSP.2007.894287        Google Scholar

16. Tropp, J. A. and A. C. Gilbert, "Signal recovery from random measurements via orthogonal matching pursuit," IEEE Transactions on Information Theory, Vol. 53, No. 12, 4655-4666, 2007.
doi:10.1109/TIT.2007.909108        Google Scholar

17. Dai, W. and O. Milenkovic, "Subspace pursuit for compressive sensing signal reconstruction," IEEE Transactions on Information Theory, Vol. 55, No. 5, 2230-2249, 2008.
doi:10.1109/TIT.2009.2016006        Google Scholar

18. Blumensath, T. and M. E. Davies, "Iterative hard thresholding for compressed sensing," Applied & Computational Harmonic Analysis, Vol. 27, No. 3, 265-274, 2008.
doi:10.1016/j.acha.2009.04.002        Google Scholar