Microwave Imaging Using SAR

Document Type : Research Article

Authors

1 MSc. Student, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran

2 Assistant Professor, Department of Electrical Engineering, Babol Noshirvani University of Technology, Babol, Iran

Abstract

Polarimetric Synthetic Aperture Radar (Pol.-SAR) allows us to implement the recognition and classification of radar targets. This article investigates the arrangement of scatterers by SAR data and proposes a new Look-up Table of Region (LTR). This look-up table is based on the combination of (entropy H/Anisotropy A) and (Anisotropy A/scattering mechanism α), which has not been reported up now. First of all, the color coded images of each of the quantities of H, A and αare extracted and then having the matrix associated with each image and evaluating its histogram, we could obtain the image parameter values corresponding to each interval related to each color code. Then in the output the combination of parameters and the sharing of their images of each frame are extracted and compared with optical images and the extracted satellite map of scattered fields. Results for unconventional targets such as random rough surfaces has indicated that mechanism of scattering irregularities and improper alignment can be used for different purposes in different parts of the frame with fixed values that can be a new method for identifying targets. To make a look up table it is essentially required to evaluate the target parameters and classification of radar images. The method of the extraction of these parameters and applying them on imaging radar systems is exclusive. To validate our work, Pol. SAR data sets are used.

Keywords

References

[1]
Storvold, R., E. Malnes, and Y. Larsen, “SAR remote sensing of snow parameters in Norwegian areas-current status and future perspective,” Journal of Electromagnetic Waves and Applications,Vol. 20, No. 13, 1751–1759, 2006.
[2]
Chan, Y. K. and S. Y. Lim, “An introduction to Synthetic Aperture Radar (SAR),” Progress in Electromagnetics Research, Vol. 2, 27–60, 2008.
[3]
Storvold, R., E. Malnes, Y. Larsen, K. A. Hogda, andS. E. Hamran, “SAR remote sensing of snow parameters in Norwegian areas-current status and future perspective,” Journal of Electromagnetic Waves and Applications, Vol. 20, No. 13, 1751–1759, 2006
[4]
Nie, X., D. Y. Zhu, and Z. D. Zhu, “Application of synthetic bandwidth approach in SAR polar format algorithm using the decamp technique,” Progress in Electromagnetics Research, PIER 80, 447–460, 2008.
[5]
Wu, B.-I., M. Yeuing, and Y. Hara, “In-SAR high in version by using 3-D phase projection with multiple baselines,” Progress InElectromagnetics Research, PIER 91, 173–193, 2009.
[6]
Lim, T. S., C.-S. Lim, and V. C. Koo, “Autofocus algorithm performance evaluations using an integrated SAR product simulator and processor,” Progress In Electromagnetics Research, PIERB, Vol. 3, 315–329, 2008.
[7]
Ebrahimi-Ganjeh, M. A. and A. R. Attari, “Study of water bolus effect on SAR penetration depth and effective field size for local hyperthermia,” Progress In Electromagnetics Research, PIER, B, Vol. 4,273–283, 2008.
[8]
S. R. Cloude, E. Pottier. “An entropy based classification scheme for land applications of Polarimetric SAR. IEEE Transactions on Geoscience and Remote Sensing, vol. 35, 1997, PP.549-557.
[9]
J .S Lee, Mo. & Grunes. Unsupervised classification using Polarimetric decomposition and the complex Wishart classifier. IEEE Transactions on Geoscience and Remote Sensing vo1.37,1999,PP.2249-2258.
[10]
E. Pottier. Unsupervised classification scheme and topography derivation of POLSAR data based on the H/α/A polarimetric decomposition theorem. In Proc. 4th International workshop on RadarPolarimetry .PP.535-548, Nantes, France, July1998.
[11]
Cloude, S. R., J. Fortuny, J. M. Lopez-Sanchez, and A. J. Sieber, “Wide-band polarimetric radar inversion studies for vegetation layers,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, No. 5, 2430–2441, 1999.
[12]
Lopez-Martinez, C., E. Pottier, and S. R. Cloude, “Statistical assessment of eigenvector-based target decomposition theorems in radar polarimetry,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 43, No. 9, 2058–2074,2005.
[13]
Cloude, S. R. and E. Pottier, “A review of target decomposition theorems in radar polarimetry,” IEEE Transactions on Geoscienceand Remote Sensing, Vol. 34, No. 2, 498–518, 1996.
[14]
J. S. Lee, M. R. Grunes. Unsupervised terrain classification preserving Polarimetric scattering characteristics. IEEE Transactions on Geoscience and Remote Sensing, vo1.42, 2004, PP.722-73I.
[15]
Zhao Li-wen, Zhou Xiao-guang, Jiang Yong-mei, Kuanggangyao. “Iterative Classification of Polarimetric SAR Image Based on the Freeman Decomposition and Scattering Entropy”. IEEE Transactions On Geoscience And Remote Sensing, vol. 7, 2007, PP.473-476.
[16]
B. Zakeri, A. Ghorbani, andH. Amindavar “A new method to extract the polarimetric parameters in imaging radars,”Progress In Electromagnetics Research, PIER 87, pp 167–182, 2008.

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