volume | PIER Journals

Abstract

Microwave array 3-D imaging is an emerging technique capable of producing a 3-D map of scattered electric fields. Its all-weather and large scene imaging features make it an attractive powerful tool for target detection and feature extraction. Typically, a microwave array 3-D imaging system based on the classical sampling theory requires a large dense 2-D antenna array, which may suffer from a very high cost. To reduce the number of the antenna array elements, this paper surveys the use of compressed sensing recovery and sparse measurement strategies for microwave array 3-D imaging. Combining with the typical spatial sparsity of the underlying scene, we pose the sparse array microwave 3-D imaging as finding sparse solutions to under-determined linear equations. Further, to reduce the computational of the compressed sensing recovery with the large-scale echoes data, we divide the underlying 3-D scene into a series of equal-range 2-D slices, and deal with these slices separately using the orthogonal matching pursuit (OMP) algorithm. Lastly, the performance of the presented compressed sensing approach is verified by an X-band microwave array 3-D imaging system. The experimental results demonstrate that the compressed sensing approach can produce a better resolution 3-D image of the observed scatterers compared with the conventional method, especially in the case of very sparse activate antenna array.

1. Peng, , X., W. Tan, Y. Wang, W. Hong, and Y. Wu, "Convolution back-projection imaging algorithm for downward-looking sparse linear array three dimensional synthetic aperture radar," Progress In Electromagnetics Research, Vol. 129, 287-313, 2012.
doi: --- Either ISSN or Journal title must be supplied. Google Scholar

2. Mohammadpoor, , M., R. S. A. Raja Abdullah, A. Ismail, and A. F. Abas, "A circular synthetic aperture radar for on-the-ground object detection ," Progress In Electromagnetics Research, Vol. 122, 269-292, 2012.
doi:10.2528/PIER11082201 Google Scholar

3. Tan, , W., W. Hong, Y. Wang, and Y. Wu, "A novel spherical-wave three-dimensional imaging algorithm for microwave cylindrical scanning geometries," Progress In Electromagnetics Research, Vol. 111, 43-70, 2011.
doi:10.2528/PIER10100307 Google Scholar

4. Huang, , Y., Y. Liu, Q. H. Liu, and J. Zhang, "Improved 3-d GPR detection by NUFFT combined with MPD method," Progress In Electromagnetics Research, Vol. 103, 185-199, 2010.
doi:10.2528/PIER10021005 Google Scholar

5. Deng, , M. Y. and X. Liu, "Electromagnetic imaging methods for nondestructive evaluation applications," Sensors , Vol. 11, No. 12, 11774-11808, 2011.
doi:10.3390/s111211774 Google Scholar

6. Zhou, , H., T. Takenaka, J. Johnson, and T. Tanaka, "A breast imaging model using microwaves and a time domain three dimensional reconstruction method," Progress In Electromagnetics Research, Vol. 93, 57-70, 2009.
doi:10.2528/PIER09033001 Google Scholar

7. Wei, , H.-Y. and M. Soleimani, "Three dimensional magnetic induction tomography imaging using a matrix free Krylov subspace inversion algorithm," Progress In Electromagnetics Research, Vol. 122, 2945, 2012. Google Scholar

8. Soleimani, , M., C. N. Mitchell, R. Banasiak, R. Wajman, and A. Adler, "Four-dimensional electrical capacitance tomography imaging using experimental data," Progress In Electromagnetics Research, Vol. 90, 171-186, 2009.
doi:10.2528/PIER09010202 Google Scholar

9. Ren, , X. Z., L. H. Qiao, and Y. Qin, "A three-dimensional imaging algorithm for tomography SAR based on improved interpolated array transform1 ," Progress In Electromagnetics Research, Vol. 120, 181-193, 2011. Google Scholar

10. Liao, , K. F., X.-L. Zhang, and J. Shi, "Fast 3-d microwave imaging method based on subaperture approximation," Progress In Electromagnetics Research, Vol. 126, 333-353, 2012.
doi:10.2528/PIER12011106 Google Scholar

11. Yu, , L. and Y. Zhang, "A 3D target imaging algorithm based on two-pass circular SAR observations," Progress In Progress In, Vol. 122, 341-360, 2012. Google Scholar

12. Shi, , J., X.-L. Zhang, J.-Y. Yang, et al. "APC trajectory design for `One-Active' linear-array three-dimensional imaging SAR," IEEE Transactions on Geoscience and Remote Sensing, Vol. 48, No. 3, 1470-1486, 2010.
doi:10.1109/TGRS.2009.2031430 Google Scholar

13. Shi, , J., X. L. Zhang, J. Yang, and K. Liao, "Experiment results on one-active LASAR," IEEE Radar Conference, 1-4, 2009. Google Scholar

14. Juan, , L. S., F. G. Joaquim, and , "3-D radar imaging using range migration techniques," IEEE Transactions on Antennas and Propagation,, Vol. 48, No. 5, 2000. Google Scholar

15. Zhang, D. H., X. L. Zhang, and , "Downward-looking 3-D linear array SAR imaging based on chirp scaling algorithm," Asian-Pacific Conference on SAR , 1043-1046, 2009. Google Scholar

16. Qi, , Y., W. Tan, Y. Wang, W. Hong, and Y. Wu, "3D bistatic omega-k imaging algorithm for near range microwave imaging systems with bistatic planar scanning geometry ," Progress In Electromagnetics Research, Vol. 121, 409-431, 2011.
doi:10.2528/PIER11090205 Google Scholar

17. Li, , S., B. Ren, H.-J. Sun, W. Hu, and X. Lv, "Modified wavenumber domain algorithm for three-dimensional millimeter-wave imaging," Progress In Electromagnetics Research,, Vol. 124, 35-53, 2012.
doi:10.2528/PIER11112406 Google Scholar

18. Montefusco, L. B., D. Lazzaro, S. Papi, and C. Guerrini, "A fast compressed sensing approach to 3D MR image reconstruction," IEEE Transactions on Medical Imaging,, Vol. 30, No. 5, 2011.
doi:10.1109/TMI.2010.2068306 Google Scholar

19. Berger, , C. R., S. L. Zhou J. C. Preisig, and P. Willett, "Sparse channel estimation for multicarrier underwater acoustic communication: From subspace methods to compressed sensing ," IEEE Transactions on Signal Processing, Vol. 58, No. 3, 2010.
doi:10.1109/TSP.2009.2038424 Google Scholar

20. Mahalanobis, A., R. Muise, and , "Object specfic image reconstruction using a compressive sensing architecture for application in surveillance systems," IEEE Transactions on Aerospace and Electronic System, Vol. 45, No. 3, 2009.
doi:10.1109/TAES.2009.5259191 Google Scholar

21. Wei, , S.-J., X.-L. Zhang, J. Shi, and G. Xiang, "Sparse reconstruction for SAR imaging based on compressed sensing," Progress In Electromagnetics Research,, Vol. 109, 63-81, 2010.
doi:10.2528/PIER10080805 Google Scholar

22. Patel, , V. M., G. R. Easley, and D. M. Healy, "Compressed synthetic aperture radar," IEEE Journal of Selected Topics in Signal Processing, Vol. 4, No. 2, 244-254, 2010.
doi:10.1109/JSTSP.2009.2039181 Google Scholar

23. Zhu, X.-X. and R. Bamler, "Tomographic SAR inversion by L1-norm regularization the compressive sensing approach," IEEE Transactions on Geoscience and Remote Sensing, Vol. 48, No. 10, 3839-3846, 2010.
doi:10.1109/TGRS.2010.2048117 Google Scholar

24. Budillon, , A., A. Evangelista, and G. Schirinzi, "Three-dimensional SAR focussing from multipass signals using compres-sive sampling ," IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 1, 488-499, 2010.
doi:10.1109/TGRS.2010.2054099 Google Scholar

25. Chen, , J., J. Gao, Y. Zhu, W. Yang, and P. Wang, "A novel image formation algorithm for high-resolution wide-swath spaceborne SAR using compressed sensing on azimuth displacement phase center antenna, ," Progress In Electromagnetics Research, Vol. 125, 527-543, 2012.
doi:10.2528/PIER11121101 Google Scholar

26. Li, J., S. Zhang, and J. Chang, "Applications of compressed sensing for multiple transmitters multiple azimuth beams SAR imaging," Progress In Electromagnetics Research, Vol. 127, 259-275, 2012.
doi:10.2528/PIER12021307 Google Scholar

27. Oliveri, , G., P. Rocca, and A. Massa, "A Bayesian-compressive-sampling-based inversion for imaging sparse scatterers," IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 10, 3993-4006, 2011.
doi:10.1109/TGRS.2011.2128329 Google Scholar

28. Poli, L., G. Oliveri, and A. Massa, "Microwave imaging within the first-order born approximation by means of the contrast-field Bayesian compressive sensing," IEEE Transactions on Antennas and Propagation, Vol. 60, No. 6, 2865-2879, 2012.
doi:10.1109/TAP.2012.2194676 Google Scholar

29. Wei, , S.-J., X.-L. Zhang, and J. Shi, "Linear array SAR imaging via compressed sensing," Progress In Electromagnetics Research,, Vol. 117, 299-319, 2011. Google Scholar

30. Donoho, , D., "Compressed sensing," IEEE Trans. Inf. Theory, Vol. 52, No. 4, 1289-1306, 2006.
doi:10.1109/TIT.2006.871582 Google Scholar

31. Candes, E. J. and M. Wakin, "An introduction to compressive sampling," IEEE Signal Processing Magazine, 21-30, 2008.
doi:10.1109/MSP.2007.914731 Google Scholar

32. Candes, , E. J., J. K. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information," IEEE Trans. Inf. Theory, Vol. 52, No. 2, 489-509, 2006.
doi:10.1109/TIT.2005.862083 Google Scholar

33. Tropp, , J. A., "Greed is good: Algrorithm results for sparse approximation ," IEEE Trans. Inf. Theory, Vol. 50, No. 10, 2231-2242, 2004.
doi:10.1109/TIT.2004.834793 Google Scholar

34. Needell, , D. and R. Vershynin, "Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit," Found. Comput. Math., Vol. 9, No. 3, 317-334, 2009.
doi:10.1007/s10208-008-9031-3 Google Scholar

35. Fornasier, , M. and H. Rauhut, "Compressive sensing," Handbook of Mathematical Methods in Imaging, Vol. 1, 187-229, 2010. Google Scholar

36. Samadi, , S., M. Cetin, and M. A. Masnadi-Shirazi, "Sparse representation-based synthetic aperture radar imaging," IET Radar, Sonar and Navigation, Vol. 5, No. 2, 182-193, 2011.
doi:10.1049/iet-rsn.2009.0235 Google Scholar

Dr. Shun-Jun Wei

Dr. Xiao-Ling Zhang

Dr. Jun Shi

Dr. Ke-Fei Liao