ASNT NDT Library

In recent years, single-frequency and wideband synthetic aperture imaging algorithms have been used in radar imaging for microwave and millimeter wave nondestructive testing (NDT) of a wide range of materials and structures. Synthetic aperture radar (SAR) techniques are robust and therefore offer great utility when incorporated with NDT applications. Unlike most radar applications, however, NDT applications are often concerned with layered composite structures in which an anomalous indication may exist. Therefore, any such SAR algorithm must be able to account for the influences of each layer according to its dielectric properties and thickness (that is, account for the influence of reflected and transmitted waves at each boundary). In such applications where small thicknesses are of interest, if the layered nature of the structure is not properly taken into account, then the image of a target may correspond to a wrong location within the structure, or may be masked or otherwise significantly altered. In this paper, an effective one-way SAR algorithm is presented that is capable of correctly imaging and determining the location of a target in an arbitrary multilayered structure. This algorithm employs spectral-domain Green’s function for a multilayered structure, which accounts for all reflected and transmitted signals at each boundary. Subsequently, a Wiener filter-based deconvolution process was employed to reconstruct an image. Reconstructed images produced in this way are devoid of unfocused and/or misplaced targets, which usually happens if standard SAR imaging techniques developed for free-space applications with homogeneous backgrounds are used for imaging a multilayered structure. This paper presents the results of simulations, as well as a representative measurement, to show the efficacy of the proposed technique.

Chew, C., Waves and Fields in Inhomogeneous Media, IEEE Press, Piscataway, New Jersey, 1995. Dehmollaian, M., M. Thiel and K. Sarabandi, “Through-the-wall Imaging Using Differential SAR,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, No. 5, May 2009, pp. 1289–1296. Dehmollaian, M. and K. Sarabandi, “Refocusing Through Building Walls Using Synthetic Aperture Radar,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 46, No. 6, January 2008, pp. 1589–1599. Fear, E. C., S. C. Hagness, P. M. Meaney, M. Okoniewski and M. A. Stuchly, “Enhancing Breast Tumor Detection with Near-field Imaging,” IEEE Microwave Magazine, Vol. 3, No. 1, March 2002, pp. 48–56. Honarvar, F., H. Sheikhzadeh, M. Moles and A. N Sinclair, “Improving the Time-Resolution and Signal-to-Noise Ratio of Ultrasonic NDE Signals,” Ultrasonics, Vol. 41, 2004, pp. 755–763. Karsli, H., “Further Improvement of Temporal Resolution of Seismic Data by Autoregressive (AR) Spectral Extrapolation,” Journal of Applied Geophysics, Vol. 59, No. 4, 2006, pp. 324–336. Kharkovsky, S., B. J. Carroll, M. T. Ghasr and R. Zoughi, “Dielectric Property Characterization of Refractory Materials Using Microwave Open- Ended and Completely Filled Waveguide Methods,” Proceedings of the Third International Conference on Electromagnetic Near-Field Characterization and Imaging, St. Louis, Missouri, August 2007. Lewis, F., “Wireless Sensor Networks: Smart Environments Technologies, Protocols, and Applications,” Data-Logging and Supervisory Control in Wireless Sensor Networks, Wiley, New York, New York, 2004. Lopez-Sanchez, J. M. and J. Fortuny-Guasch, “3D Radar Imaging Using Range Migration Techniques,” IEEE Transactions on Antennas and Propagation, Vol. 48, No. 5, May 2000, pp. 728–737. Meng, D., V. Sethu, E. Ambikairajah and L. Ge, “A Novel Technique for Noise Reduction in InSAR Images,” IEEE Geoscience and Remote Sensing Letters, Vol. 4, No. 2, April 2007, pp. 226–230. Piles, M., A. Camps, M. Vall-llossera, A. Monerris, M. Talone and J. L. A. Perez, “Deconvolution Algorithms in Image Reconstruction for Aperture Synthesis Radiometers,” IEEE Geoscience and Remote Sensing Symposium, 23 – 28 July 2007, pp. 1460–1463. Sheen, D. M., D. L. McMakin and T. E. Hall, “Three-dimensional Millimeter-wave Imaging for Concealed Weapon Detection,” IEEE Transactions on Microwave Theory and Techniques, Vol. 49, No. 9, September 2001, pp. 1581–1592. Sin, S. K. and C. H. Chen, “A comparison of Deconvolution Techniques for The Ultrasonic Nondestructive Evaluation of Materials,” IEEE Transactions on Image Processing, Vol. 1, No. 1, January 1992, pp. 3–10. Solbo, S. and T. Eltoft, “A Stationary Wavelet-Domain Wiener Filter for Correlated Speckle,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 46, No. 4, April 2008, pp. 1219–1230. Song, L. P., Q. H. Liu, F. Li and Z. Q. Zhang, “Reconstruction of Three- Dimensional Objects in Layered Media: Numerical Experiments,” IEEE Transactions on Antennas and Propagation, Vol. 53, No. 4, April 2005, pp. 1556–1561. Soumekh, M., Synthetic Aperture Radar Signal Processing with MATLAB Algorithms, 1st ed., Wiley, 1999, New York, New York. Vossiek, M., A. Urban, S. Max and P. Gulden, “Inverse Synthetic Aperture Secondary Radar Concept for Precise Wireless Positioning,” IEEE Transactions on Microwave Theory and Techniques, Vol. 55, No. 11, November 2007, pp. 2447–2453. Wiener, N., Extrapolation, Interpretation, and Smoothing of Stationary Time Series with Engineering Application, M.I.T. Press and John Wiley and Sons, 1949. Yu, C., M. Yuan, Y. Zhang, J. Stang, R. T. George, G. A. Ybarra, W. T. Joines, W. T. and Q. H. Liu, “Microwave Imaging in Layered Media: 3-D Image Reconstruction from Experimental Data,” IEEE Transactions on Antennas and Propagation, Vol. 58, No. 2, February 2010, pp. 440–448. Yu, C., M. Yuan, J. Stang, E. Bresslour, R. T. George, G. A. Ybarra, W. T. Joines and Q. H. Liu, “Active Microwave Imaging II: 3-D System Prototype and Imaging Reconstruction from Experimental Data,” IEEE Transactions on Microwave Theory and Techniques, Vol. 56, No. 4, April 2008, pp. 991–1000.

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