News

 Statistics

Number of Journals34
Number of Issues1,306
Number of Articles9,427
Article View9,188,974
PDF Download5,621,548
Salehi Barzegar, A., Cheldavi, A. (2020). Three Dimensional Through the Wall Radar Imaging Using Compressed Sensing. Electronic and Cyber Defense, 7(2), 111-118.
Alireza Salehi Barzegar; Ahmad Cheldavi. "Three Dimensional Through the Wall Radar Imaging Using Compressed Sensing". Electronic and Cyber Defense, 7, 2, 2020, 111-118.
Salehi Barzegar, A., Cheldavi, A. (2020). 'Three Dimensional Through the Wall Radar Imaging Using Compressed Sensing', Electronic and Cyber Defense, 7(2), pp. 111-118.
Salehi Barzegar, A., Cheldavi, A. Three Dimensional Through the Wall Radar Imaging Using Compressed Sensing. Electronic and Cyber Defense, 2020; 7(2): 111-118.

Three Dimensional Through the Wall Radar Imaging Using Compressed Sensing

رادار
Article 11, Volume 7, Issue 2 - Serial Number 22, July 2020, Pages 111-118    PDF (1.2 M)
Document Type: Original Article
Authors
Alireza Salehi Barzegar* 1; Ahmad Cheldavi2
1PhD student, Faculty of Electrical Engineering, University of Science and Technology, Tehran, Iran
2Professor, Faculty of Electrical Engineering, University of Science and Technology, Tehran, Iran
Receive Date: 24 December 2019,  Revise Date: 17 May 2020,  Accept Date: 12 July 2020 
Abstract
In this paper, the compressive sensing (CS) method is used in the through the wall radar imaging (TWRI) to reduce the measurement points and data acquisition time, consequently. In fact, the large required amount of measurement points is considered as one of the main challenges in TWRI which can be mitigated by this proposed method. The diffraction tomography (DT) method is the most effeicient conventional method used in TWRI process. By exploiting the advantages of the CS and non uniform fast Fourier transform (NUFFT), the effectiveness and speediness of the DT method is significantly increased. Simulation and experiment results have verified the validity of the proposed imaging method.
Keywords
through-the-wall radar imaging (TWRI); diffraction tomography (DT); Compressed Sensing (CS); Nonuniform fast Fourier transform (NUFFT)
References

   [1]      F.  Ahmad and M.  G.  Amin, “Noncoherent approach to through-the-wall radar localization,” IEEE Trans. Aerosp. Electron. Syst., vol. 42, no. 4, pp. 1405–1419, Oct. 2006

   [2]      F. Ahmad, M. G. Amin, and S. A. Kassam, “Synthetic aperture beam-former f or imaging through a d ielectric wall,” IEEE Trans. Aerosp. Elec-tron. Syst., vol. 41, no. 1, pp. 271–283, Jan. 2005.

   [3]      F. Ahmad, Y. Zhang, and M. Amin, “Three-dimensional wideband b eam-forming for imaging through a single wall,” IEEE Geosci. Remote Sensing Lett., vol. 5, no. 2, pp. 176–179, Apr. 2008.

   [4]      L. P. Song, C. Yu , and Q. H. Liu, “Through-wall imaging (TWI) by radar: 2-D tomographic results and analyses,” IEEE Trans. Geosci. Remote Sens., vol. 43, no. 12, pp. 2793–2798, Dec. 2005.

   [5]      F. Soldovieri and  R. Solimene, “Through-wall imaging via  a linear inverse scattering  algorithm,” IEEE Geosci. Remote Sensing Lett., vol. 4 , no. 4, pp. 513–517, Oct. 2007.

   [6]      W. Zhang, A.  Hoorfar, and L. Li, “Through-the-wall  target  localization with  time  reversal  music method,” Progr. Electromagn. Res., vol. 106, pp. 75–89, 2010.

   [7]      W. Zhang, A. Hoorfar, C. Thajudeen, and F. Ahmad, “Full polarimetric beam-forming algorithm for through-the-wall radar imaging,” Radio Sci., vol. 46, pp.                      RS0E16-1–RS0E16-17, Oct. 2011.

   [8]      W. Zhang, A.  Hoorfar, and Q.  H.  Liu, “Three dimensional  imaging of targets behind multilayered walls,” in Proc. IEEE Int. Symp. APSURSI , Chicago, IL, pp. 1–2, 2012.

   [9]      W. J. Zhang and A. Hoorfar, “Three-dimensional real-time through-the-wall radar imaging with diffraction tomographic algorithm,” IEEE Trans. Geosci. Remote Sens., vol. 51, no. 7, pp. 4155-4163, Jul. 2013.

[10]      J. Yang, T. Jin, X. Huang, J. Thompson, and Z. Zhou, “Sparse MIMO array forward-looking GPR imaging based on compressed sensing in clutter environment,” IEEE Trans. Geosci. Remote Sens., vol. 52, no. 7, pp.           4480–4494, Jul. 2014.

[11]      M. Lustig, D. Donoho, and J. Pauly, “Sparse MRI: The application of compressed sensing for rapid MR imaging,” Magn. Reson. Med., vol. 58, no. 6, pp. 1182–1195, Dec. 2007.

[12]      W. Zhang, M. G. Amin, F. Ahmad, A. Hoorfar, and G. E. Smith, “Ultrawideband impulse radar through-the-wall imaging with compressive sensing,” Int. J. Antennas Propag., vol. 2012, Feb. 2012, Art. no. 251497, doi: 10.1155/2012/251497.

[13]      T. B. Hansen and P. M. Johansen, “Inversion scheme f or monostatic ground penetrating r adar that takes into account the p lanar air-soil interface,” IEEE Trans. Geosci. Remote Sens., vol. 38, no. 1, pp. 496–506, Jan. 2000.

[14]      Z. Yang and Y. R. Zheng, “Near-field 3-D synthetic aperture radar imaging via compressed sensing,” in Proc. IEEE ICASSP, Kyoto, pp. 2513-2516, 2012.

[15]      A. Dutt and V. Rokhlin, “Fast Fourier transforms for nonequispaced data,” SIAM J. Sci. Comput., vol. 14, no. 6, pp. 1368–1393, Nov.1993.

[16]      L. Greengard and J.-Y. Lee, “Accelerating the nonuniform fast Fourier transform,” SIAM Rev., vol. 46, no. 3, pp. 443–454, 2004. 

[17]      J. Song, Q. H. Liu, K. Kim, and W. Scott, “High-resolution 3-D radar imaging through nonuniform fast Fourier transform (NUFFT),” Commun. Comput. Phys., vol. 1, no. 1, pp. 176–191, Feb. 2006.

[18]      D. S. Smith, S. Sengupta, S. A. Smith, and E. Brian Welch, “Trajectory optimized NUFFT: Faster non-cartesian MRI reconstruction through prior knowledge and parallel architectures,” Magn. Reson. Med, vol. 81, no. 3, pp. 2064–2071, Oct. 2019.

[19]      D. Sun, S. Xing, Y. Li, B. Pang, and X. Wang,             “Sub-aperture partition-ing method for three-dimensional wide-angle synthetic aperture radar imaging with           non-uniform sampling,” Electronics, vol. 8, no. 6, pp. 629, Jun. 2019.

[20]      P. Zhang, P. Fei, X. Wen, and F. Nian, “A novel      through-the-wall imaging algorithm combined with phase shift migration and NUFFT,” Chinese Journal of Electronics, vol. 26, no. 5, pp. 1096–1100, 2017.

[21]      L. Yuan, J. Liu, and J. Ye, “Efficient methods for overlapping group Lasso,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 9, pp. 2104-2116, Sept. 2013.

[22]      J. A. Tropp and A. C. Gilbert, “Signal recovery from random measurements via orthogonal matching pursuit,” IEEE Trans. Inf. Theory, vol. 53, no. 12, pp. 4655–4666, Dec. 2007.

[23]      M. Dehmollaian and K. Sarabandi, “Refocusing through bu ilding walls using synthetic aperture radar,” IEEE Trans. Geosci. Remote Sens., vo l. 46, no. 6, pp. 1589–1599, Jun. 2008.

Statistics
Article View: 671
PDF Download: 423