Abstract

We propose a polarimetric microwave imaging technique that exploits recent advances in computational imaging. We utilize a frequency-diverse cavity-backed metasurface, allowing us to demonstrate high-resolution polarimetric imaging using a single transceiver and frequency sweep over the operational microwave bandwidth. The frequency-diverse metasurface imager greatly simplifies the system architecture compared with active arrays and other conventional microwave imaging approaches. We further develop the theoretical framework for computational polarimetric imaging and validate the approach experimentally using a multi-modal leaky cavity. The scalar approximation for the interaction between the radiated waves and the target— often applied in microwave computational imaging schemes—is thus extended to retrieve the susceptibility tensors, and hence provides additional information about the targets. Computational polarimetry has relevance for existing systems in the field that extract polarimetric imagery, and particular for ground observation. A growing number of short-range microwave imaging applications can also notably benefit from computational polarimetry, particularly for imaging objects that are difficult to reconstruct when assuming scalar estimations.

© 2017 Optical Society of America

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References

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2017 (2)

J. Gollub, O. Yurduseven, K. Trofatter, D. Arnitz, M. Imani, T. Sleasman, M. Boyarsky, A. Rose, A. Pedross-Engel, H. Odabasi, T. Zvolensky, G. Lipworth, D. Brady, D. L. Marks, M. S. Reynolds, and D. R. Smith, “Large metasurface aperture for millimeter wave computational imaging at the human-scale,” Sci. Rep. 7, 42650 (2017).
[Crossref] [PubMed]

O. Yurduseven, D. L. Marks, T. Fromenteze, J. N. Gollub, and D. R. Smith, “Millimeter-wave spotlight imager using dynamic holographic metasurface antennas,” Opt. Express 25, 18230–18249 (2017).
[Crossref] [PubMed]

2016 (7)

T. Fromenteze, X. Liu, M. Boyarsky, J. Gollub, and D. R. Smith, “Phaseless computational imaging with a radiating metasurface,” Opt. Express 24, 16760–16776 (2016).
[Crossref] [PubMed]

O. Yurduseven, J. N. Gollub, D. L. Marks, and D. R. Smith, “Frequency-diverse microwave imaging using planar mills-cross cavity apertures,” Opt. Express 24, 8907–8925 (2016).
[Crossref] [PubMed]

D. L. Marks, J. Gollub, and D. R. Smith, “Spatially resolving antenna arrays using frequency diversity,” J. Opt. Soc. Am. A 33, 899–912 (2016).
[Crossref]

T. Fromenteze, E. L. Kpré, D. Carsenat, C. Decroze, and T. Sakamoto, “Single-shot compressive multiple-inputs multiple-outputs radar imaging using a two-port passive device,” IEEE Access 4, 1050–1060 (2016).
[Crossref]

A. Abbosh, B. Mohammed, and K. Bialkowski, “Differential microwave imaging of the breast pair,” IEEE Antennas Wireless Propag. Lett 15, 1434–1437 (2016).
[Crossref]

B. Gonzalez-Valdes, Y. Álvarez, Y. Rodriguez-Vaqueiro, A. Arboleya-Arboleya, A. García-Pino, C. M. Rappaport, F. Las-Heras, and J. A. Martinez-Lorenzo, “Millimeter wave imaging architecture for on-the-move whole body imaging,” IEEE Trans. Antennas Propag. 64, 2328–2338 (2016).
[Crossref]

J. Wang, P. Aubry, and A. Yarovoy, “A novel approach to full-polarimetric short-range imaging with copolarized data,” IEEE Trans. Antennas Propag. 64, 4733–4744 (2016).
[Crossref]

2015 (3)

G. Lipworth, A. Rose, O. Yurduseven, V. R. Gowda, M. F. Imani, H. Odabasi, P. Trofatter, J. Gollub, and D. R. Smith, “Comprehensive simulation platform for a metamaterial imaging system,” Appl. Opt. 54, 9343–9353 (2015).
[Crossref] [PubMed]

O. Yurduseven, M. F. Imani, H. Odabasi, J. Gollub, G. Lipworth, A. Rose, and D. R. Smith, “Resolution of the frequency diverse metamaterial aperture imager,” Prog. Electromag. Res. 150, 97–107 (2015).
[Crossref]

T. Fromenteze, O. Yurduseven, M. F. Imani, J. Gollub, C. Decroze, D. Carsenat, and D. R. Smith, “Computational imaging using a mode-mixing cavity at microwave frequencies,” Appl. Phys. Lett. 106, 194104 (2015).
[Crossref]

2014 (1)

Y. Rodriguez-Vaqueiro, Y. A. Lopez, B. Gonzalez-Valdes, J. A. Martinez, F. Las-Heras, and C. M. Rappaport, “On the use of compressed sensing techniques for improving multistatic millimeter-wave portal-based personnel screening,” IEEE Trans. Antennas Propag. 62, 494–499 (2014).
[Crossref]

2013 (3)

J. Hunt, T. Driscoll, A. Mrozack, G. Lipworth, M. Reynolds, D. Brady, and D. R. Smith, “Metamaterial apertures for computational imaging,” Science 339, 310–313 (2013).
[Crossref] [PubMed]

G. Lipworth, A. Mrozack, J. Hunt, D. L. Marks, T. Driscoll, D. Brady, and D. R. Smith, “Metamaterial apertures for coherent computational imaging on the physical layer,” J. Opt. Soc. Am. A 30, 1603–1612 (2013).
[Crossref]

D. Velotto, F. Nunziata, M. Migliaccio, and S. Lehner, “Dual-polarimetric terrasar-x sar data for target at sea observation,” IEEE Geosci. Remote Sens. Lett. 10, 1114–1118 (2013).
[Crossref]

2012 (4)

R. K. Amineh, A. Khalatpour, and N. K. Nikolova, “Three-dimensional microwave holographic imaging using co-and cross-polarized data,” IEEE Trans. Antennas Propag. 60, 3526–3531 (2012).
[Crossref]

D. Carsenat and C. Decroze, “Uwb antennas beamforming using passive time-reversal device,” IEEE Antennas Wireless Propag. Lett 11, 779–782 (2012).
[Crossref]

S. S. Ahmed, A. Schiessl, F. Gumbmann, M. Tiebout, S. Methfessel, and L. Schmidt, “Advanced microwave imaging,” IEEE Microw. Mag. 13, 26–43 (2012).
[Crossref]

Y. Wang and A. E. Fathy, “Advanced system level simulation platform for three-dimensional uwb through-wall imaging sar using time-domain approach,” IEEE Trans. Geosci. Remote Sens. 50, 1986–2000 (2012).
[Crossref]

2011 (5)

X. Zhuge and A. G. Yarovoy, “A sparse aperture mimo-sar-based uwb imaging system for concealed weapon detection,” IEEE Trans. Geosci. Remote Sens. 49, 509–518 (2011).
[Crossref]

S. S. Ahmed, A. Schiessl, and L.-P. Schmidt, “A novel fully electronic active real-time imager based on a planar multistatic sparse array,” IEEE Trans. Microw. Theory Techn. 59, 3567–3576 (2011).
[Crossref]

N. K. Nikolova, “Microwave imaging for breast cancer,” IEEE Microw. Mag. 12, 78 (2011).

G. Bellizzi, O. M. Bucci, and I. Catapano, “Microwave cancer imaging exploiting magnetic nanoparticles as contrast agent,” IEEE Trans. Biomed. Eng. 58, 2528–2536 (2011).
[Crossref] [PubMed]

J. J. van Zyl, M. Arii, and Y. Kim, “Model-based decomposition of polarimetric sar covariance matrices constrained for nonnegative eigenvalues,” IEEE Trans. Geosci. Remote Sens. 49, 3452–3459 (2011).
[Crossref]

2010 (1)

2009 (2)

M. Dehmollaian, M. Thiel, and K. Sarabandi, “Through-the-wall imaging using differential sar,” IEEE Trans. Geosci. Remote Sens. 47, 1289–1296 (2009).
[Crossref]

U. Hasar, “Non-destructive testing of hardened cement specimens at microwave frequencies using a simple free-space method,” NDT and E Int. 42, 550–557 (2009).
[Crossref]

2008 (2)

T. C. Williams, J. M. Sill, and E. C. Fear, “Breast surface estimation for radar-based breast imaging systems,” IEEE Trans. Biomed. Eng. 55, 1678–1686 (2008).
[Crossref] [PubMed]

E. J. Baranoski, “Through-wall imaging: Historical perspective and future directions,” J. Franklin Inst. 345, 556–569 (2008).
[Crossref]

2007 (2)

T. Rubæk, P. M. Meaney, P. Meincke, and K. D. Paulsen, “Nonlinear microwave imaging for breast-cancer screening using gauss–newton’s method and the cgls inversion algorithm,” IEEE Trans. Antennas Propag. 55, 2320–2331 (2007).
[Crossref]

S. Kharkovsky and R. Zoughi, “Microwave and millimeter wave nondestructive testing and evaluation-overview and recent advances,” IEEE Instrum. Meas. Mag. 10, 26–38 (2007).
[Crossref]

2006 (2)

M. Benedetti, M. Donelli, A. Martini, M. Pastorino, A. Rosani, and A. Massa, “An innovative microwave-imaging technique for nondestructive evaluation: applications to civil structures monitoring and biological bodies inspection,” IEEE Trans. Instrum. Meas. 55, 1878–1884 (2006).
[Crossref]

S. Mori and J. Zhang, “Principles of diffusion tensor imaging and its applications to basic neuroscience research,” Neuron 51, 527–539 (2006).
[Crossref] [PubMed]

2004 (2)

G. Montaldo, D. Palacio, M. Tanter, and M. Fink, “Time reversal kaleidoscope: A smart transducer for three-dimensional ultrasonic imaging,” Appl. Phys. Lett. 84, 3879–3881 (2004).
[Crossref]

S. Caorsi, A. Massa, M. Pastorino, and M. Donelli, “Improved microwave imaging procedure for nondestructive evaluations of two-dimensional structures,” IEEE Trans. Antennas Propag. 52, 1386–1397 (2004).
[Crossref]

2002 (4)

E. C. Fear, X. Li, S. C. Hagness, and M. A. Stuchly, “Confocal microwave imaging for breast cancer detection: Localization of tumors in three dimensions,” IEEE Trans. Biomed. Eng. 49, 812–822 (2002).
[Crossref] [PubMed]

A. Abubakar, P. M. Van den Berg, and J. J. Mallorqui, “Imaging of biomedical data using a multiplicative regularized contrast source inversion method,” IEEE Trans. Microw. Theory Techn. 50, 1761–1771 (2002).
[Crossref]

P.-S. Kildal, K. Rosengren, J. Byun, and J. Lee, “Definition of effective diversity gain and how to measure it in a reverberation chamber,” Microw. Opt. Technol. Lett 34, 56–59 (2002).
[Crossref]

D. A. Hill and J. M. Ladbury, “Spatial-correlation functions of fields and energy density in a reverberation chamber,” IEEE Trans. Electromagn. Compat 44, 95–101 (2002).
[Crossref]

2001 (2)

D. Le Bihan, J.-F. Mangin, C. Poupon, C. A. Clark, S. Pappata, N. Molko, and H. Chabriat, “Diffusion tensor imaging: concepts and applications,” J. Mag. Res. Imag. 13, 534–546 (2001).
[Crossref]

D. M. Sheen, D. L. McMakin, and T. E. Hall, “Three-dimensional millimeter-wave imaging for concealed weapon detection,” IEEE Trans. Microw. Theory Techn. 49, 1581–1592 (2001).
[Crossref]

2000 (1)

R. N. Treuhaft and P. R. Siqueira, “Vertical structure of vegetated land surfaces from interferometric and polarimetric radar,” Radio Sci. 35, 141–177 (2000).
[Crossref]

1997 (1)

C. Draeger and M. Fink, “One-channel time reversal of elastic waves in a chaotic 2d-silicon cavity,” Phys. Rev. Lett. 79, 407 (1997).
[Crossref]

1994 (1)

P. J. Basser, J. Mattiello, and D. LeBihan, “Mr diffusion tensor spectroscopy and imaging,” Biophys. J. 66, 259–267 (1994).
[Crossref] [PubMed]

Abbosh, A.

A. Abbosh, B. Mohammed, and K. Bialkowski, “Differential microwave imaging of the breast pair,” IEEE Antennas Wireless Propag. Lett 15, 1434–1437 (2016).
[Crossref]

Abubakar, A.

A. Abubakar, P. M. Van den Berg, and J. J. Mallorqui, “Imaging of biomedical data using a multiplicative regularized contrast source inversion method,” IEEE Trans. Microw. Theory Techn. 50, 1761–1771 (2002).
[Crossref]

Ahmed, S. S.

S. S. Ahmed, A. Schiessl, F. Gumbmann, M. Tiebout, S. Methfessel, and L. Schmidt, “Advanced microwave imaging,” IEEE Microw. Mag. 13, 26–43 (2012).
[Crossref]

S. S. Ahmed, A. Schiessl, and L.-P. Schmidt, “A novel fully electronic active real-time imager based on a planar multistatic sparse array,” IEEE Trans. Microw. Theory Techn. 59, 3567–3576 (2011).
[Crossref]

Álvarez, Y.

B. Gonzalez-Valdes, Y. Álvarez, Y. Rodriguez-Vaqueiro, A. Arboleya-Arboleya, A. García-Pino, C. M. Rappaport, F. Las-Heras, and J. A. Martinez-Lorenzo, “Millimeter wave imaging architecture for on-the-move whole body imaging,” IEEE Trans. Antennas Propag. 64, 2328–2338 (2016).
[Crossref]

Amineh, R. K.

R. K. Amineh, A. Khalatpour, and N. K. Nikolova, “Three-dimensional microwave holographic imaging using co-and cross-polarized data,” IEEE Trans. Antennas Propag. 60, 3526–3531 (2012).
[Crossref]

Arboleya-Arboleya, A.

B. Gonzalez-Valdes, Y. Álvarez, Y. Rodriguez-Vaqueiro, A. Arboleya-Arboleya, A. García-Pino, C. M. Rappaport, F. Las-Heras, and J. A. Martinez-Lorenzo, “Millimeter wave imaging architecture for on-the-move whole body imaging,” IEEE Trans. Antennas Propag. 64, 2328–2338 (2016).
[Crossref]

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D. M. Sheen, D. L. McMakin, and T. E. Hall, “Three-dimensional millimeter-wave imaging for concealed weapon detection,” IEEE Trans. Microw. Theory Techn. 49, 1581–1592 (2001).
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Figures (15)

Fig. 1
Fig. 1 Polarimetric radar system: Two arrays made of dual-polarized antennas are used in transmission and reception for interrogating the susceptibility tensor χ̄(r) in the target space. To estimate the image, the fields radiated by each antennas must be known—either measured or derived (e.g. from the propagation of the surface currents with the dyadic Green’s functions G(rrt,r, ν).
Fig. 2
Fig. 2 Radiating metasurface implemented for the demonstration of microwave computational polarimetry. The current distribution is shown on the aperture and represents an excitation of the transmission port at a single frequency. The metasurface is conceived to obtain pseudo-orthogonal current distributions in the frequency domain.
Fig. 3
Fig. 3 Description of the susceptibility tensor with a mechanical model of the bound electron. The induced polarization corresponds to a motion of these particles reacting to an electric field. This tensor is diagonalized by the compensation of the rotation between the radiated wave’s axis (red) and the main axis of the electron (black) confined in its movements by the interaction with the surrounding particles.
Fig. 4
Fig. 4 Ellipsoids representing the eigenvalues/eigenvectors decomposition of the electric susceptibility tensor estimated for each voxel. The anisotropic scattering is represented by an ellipsoid with axis of unequal lengths, depicting the local orientation of the tensor.
Fig. 5
Fig. 5 Analysis of the field generated by one dipole of the transmitting (a) and receiving (b) current distributions at the same location r0.
Fig. 6
Fig. 6 Radiating metasurface implemented for the validation of the proposed computational polarimetric imaging technique. The radiated near-field is measured on both transverse polarizations with a single-polarized open-ended waveguide probe.
Fig. 7
Fig. 7 Near-field scans measured by a raster scan back-propagated to the aperture of the metasurface. The real part of the fields are represented for each excitation port and two consecutive frequencies just above 25 GHz, spaced by only 2.5 MHz.
Fig. 8
Fig. 8 Autocorrelation of the processed near field scan obtained on the x-polarization when feeding the port 1 of the cavity.
Fig. 9
Fig. 9 Spatial correlation of the near field scans represented for each couple of ports and polarizations. The axis have been removed to save space and are equivalent for each sub-figure to these of Fig. 8
Fig. 10
Fig. 10 Copper wire letters used as targets. Each letter is 15 × 9 cm2.
Fig. 11
Fig. 11 Three-dimensional estimation of the full susceptibility tensor χ ¯ ^ of the first target. The opacity of each voxel is coded on a log scale with a −15 dB minimum threshold.
Fig. 12
Fig. 12 Susceptibility tensor extracted from the target plane. The opacity of the pixels corresponds to the linear magnitude of the tensor. The phase is color-coded.
Fig. 13
Fig. 13 Correlation of two co-polarized transverse components of χ̂corr. The opacity of the figure corresponds to the magnitude of χ̂corr and the color coding of the phase of χ̂corr.
Fig. 14
Fig. 14 Three-dimensional estimation of χ̂corr. A −20 dB isosurface is represented, color-coded according to the phase of χ̂corr.
Fig. 15
Fig. 15 Set of ellipsoids obtained by computing eigendecompositions of the real (left) and imaginary (right) parts of the retrieved susceptibility tensor.

Equations (21)

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S x , z ( r t , r r , ν ) = r E x ( r t , r , ν ) χ ¯ ( r ) E z ( r r , r , ν ) T d 3 r
S ¯ ( r t , r r , ν ) = r E ¯ ( r t , r , ν ) χ ¯ ( r ) E ¯ ( r r , r , ν ) T d 3 r
2 A t , r ( r t , r , ν ) + k 2 A t , r ( r t , r , ν ) = μ 0 J t , r ( r t , r , ν )
A t , r ( r , ν ) = μ 0 r t , r J t , r ( r t , r , ν ) g ( r r t , r , ν ) d 3 r t , r
E t , r ( r , ν ) = j c k [ ( A t , r ( r , ν ) ) + k 2 A t , r ( r , ν ) ]
= j 2 π ν μ 0 r t , r J t , r ( r t , r , ν ) G ¯ ( r , r t , r , ν ) d 3 r t , r
G ¯ ( r a , r b , ν ) = ( I ¯ + k 2 ) { g ( r a r b , ν ) }
s ( ν ) = j π 0 ν r E r ( r , ν ) χ ¯ ( r ) E t ( r , ν ) T d 3 r
= j π 0 ν r Tr [ χ ¯ ( r ) E r ( r , ν ) E t ( r , ν ) T ] d 3 r
χ ¯ ( r ) = R ¯ ( r ) diag ( ξ ( r ) ) R ¯ ( r ) T
p t , r ( r t , r ) = 0 n r t , r ( y ^ E t , r tan ( r t , r , ν ) ) d 2 r t , r
m t , r ( r t , r ) = 1 j μ π ν r t , r ( n × E t , r tan ( r t , r , ν ) ) d 2 r t , r
E t , r ( r , ν ) = μ 0 π ν 2 c r t , r [ r × m t , r ( r t , r ) ] g ( r t , r r , ν )
r × m t , r ( r t , r ) = [ 0 z y z 0 x y x 0 ] [ m x 0 m z ] = [ y m z z m x x m z x m y y m x ]
χ ¯ ^ ( r ) = ν ν j π 0 E r ( r , ν ) + s ( ν ) E t ( r , ν ) + T
χ ¯ ^ ( m , n ) ( r 0 ) = ν ν j π 0 E r , m ( r 0 , ν ) + s ( ν ) E t , n ( r 0 , ν ) + T
= p , q χ ¯ ( p , q ) ( r 0 ) R ( m , n , p , q ) ( r 0 )
R ( m , n , p , q ) ( r 0 ) = ν r E r , m ( r 0 , ν ) + E r , p ( r , ν ) E t , p ( r , ν ) T E t , n ( r 0 , ν ) + T d 3 r
R ( m , n , p , q ) ( r 0 ) = { 1 , if ( m , n ) = ( p , q ) 0 if ( m , n ) ( p , q )
C 1 , 2 ( r t , r t ) = 𝔼 [ ( E 1 ) ] 𝔼 [ ( E 2 ) ] σ 1 σ 2
χ ^ corr ( r ) = χ ^ x , x χ ^ z , z *

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