سابِق|تال

Comparison of performance of radar imaging under condition of obscured by random media

  • role： First author第一作者
  • Affiliation：

    The State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：yity@radi.ac.cn
  • Introduction：伊铁延，1991年生，男，博士研究生，研究方向为微波成像理论。E-mail： yity@radi.ac.cn
YI Tieyan12,  
  • role： Corresponding author通信作者
  • Affiliation：

    The State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

  • Email：chenks@radi.ac.cn
  • Introduction：陈锟山，1959年生，男，研究员，研究方向为微波遥感。E-mail： chenks@radi.ac.cn
CHEN Kunshan1*,  
  • Affiliation：

    The State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

LIU Yu1

ملخص

Radar imaging of objects obscured by random media is an important issue because of its wide application in the fields of geography, medicine, and the military. However, the echo signals from the observed target(s) may be severely distorted because of the presence of random media (e.g., vegetation, atmospheric turbulence, biological tissues, or walls), thereby eventually degrading imaging quality. To obtain higher resolution, imaging technology that works in the millimeter wave or even a higher frequency band is desirable. However, the electromagnetic wave in this frequency band is more heavily affected by random media and is more susceptible to attenuation, which hinders the application of millimeter wave radar remote sensing. This limitation further highlights the urgency of research on the imaging of objects obscured by random media. Therefore, evaluating and improving the imaging performance fully and ultimately are especially important.Synthetic Aperture Radar (SAR) technology has been widely used in many fields, especially for remote sensing, since its introduction in the 1950s. Scholars have proposed different imaging algorithms and used the obtained data to analyze the dielectric properties and geometric characteristics of the observed target (e.g., INSAR, POL-SAR, POL-INSAR, and TOMO-SAR). Alternatively, some imaging technology employs the time symmetry of the field (electromagnetic or acoustics) wave equation and the reciprocity of the Green’s function to locate and imaging the targets. In particular, the Time Reversal (TR) method allows us to selectively focus on different targets separately, whereas the Time Reversal-Multiple Signal Classification (TR-MUSIC) method improves the imaging resolution greatly. However, current studies are often limited to a specific field, and research on the comparison of the performance of different methods is relatively rare. Therefore, in this paper, these typical radar imaging methods are selected to evaluate their performance toward imaging the target obscured by random media. Given that the target is obscured by random media, describing the effects caused by random media on the propagation of the electromagnetic wave is necessary. According to the radiation transfer equation, the attenuation of electromagnetic waves caused by random medium is related to optical thickness, which is equal to the sum of the scattering and absorption thickness. The model will be used to describe the interaction of electromagnetic waves with random media. For quantitative evaluation, 3 dB beam-width and the geometric location of a point target response are used.Although the results in the three methods are all degraded by the presence of random media, TR-MUSIC performs the best followed by SAR and TR. The effects of scattering thickness is the main factor that causes imaging degradation, whereas the degradation caused by absorption thickness is very weak. In summary, this phenomenon is due to the clutter enhancement from random media when the scattering thickness increases, while the effects of absorption thickness correspond to the energy of electromagnetic waves being absorbed. Among the three techniques, TR and TR-MUSIC can suppress the grating lobes better than SAR does under a sparse array, and TR-MUSIC delivers the best imaging performance.Considering the advantages of TR-MUSIC in the performance and the side lobe suppression, we focus on improving its performance further. Based on theoretical analysis, some centrally located array elements are removed to undermine clutters, and better imaging results are obtained for TR-MUSIC.

مفهوم

radar imaging;Random Medium;Comparative Analysis;synthetic aperture radar (SAR);Time Reversal Imaging

References

  1. 1.
    Bamler R and Hartl P. 1998. Synthetic aperture radar interferometry. Inverse Problems, 14(4): R1-R54
  2. 2.
    Chang J M, Jin M, Zeng J Y and Chen K S. 2018. Analysis on time reversal imaging in presence of random media. Journal of University of Chinese Academy of Sciences, 35(1): 59-65
  3. 3.
    Chang Y L, Chiang C Y and Chen K S. 2011. SAR image simulation with application to target recognition. Progress in Electromagnetics Research, 119: 35-57
  4. 4.
    Chen K S. 2015. Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach. Boca Raton: CRC Press
  5. 5.
    Cloude S R and Papathanassiou K P. 1998. Polarimetric SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 36(5): 1551-1565
  6. 6.
    Cumming I G and Wong F H. 2005. Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation. Norwood: Artech House
  7. 7.
    Dehmollaian M and Sarabandi K. 2008. Refocusing through building walls using synthetic aperture radar. IEEE Transactions on Geoscience and Remote Sensing, 46(6): 1589-1599
  8. 8.
    Devaney A J. 2005. Time reversal imaging of obscured targets from multistatic data. IEEE Transactions on Antennas and Propagation, 53(5): 1600-1610
  9. 9.
    Fouda A E, Lopez-Castellanos V and Teixeira F L. 2014. Experimental demonstration of statistical stability in ultrawideband time-reversal imaging. IEEE Geoscience and Remote Sensing Letters, 11(1): 29-33
  10. 10.
    Goodman J W. 1985. Statistical Optics. New York: John Wiley and Sons
  11. 11.
    Ishimaru A. 1978. Wave Propagation and Scattering in Random Media. New York: Academic Press
  12. 12.
    Ishimaru A. 1991. Wave propagation and scattering in random media and rough surfaces. Proceedings of the IEEE, 79(10): 1359-1366
  13. 13.
    Ishimaru A, Jaruwatanadilok S and Kuga Y. 2004. Multiple scattering effects on the radar cross section (RCS) of objects in a random medium including backscattering enhancement and shower curtain effects. Waves in Random Media, 14(4): 499-511
  14. 14.
    Ishimaru A, Jaruwatanadilok S and Kuga Y. 2007. Imaging of a target through random media using a short-pulse focused beam. IEEE Transactions on Antennas and Propagation, 55(6): 1622-1629
  15. 15.
    Ishimaru A, Jaruwatanadilok S and Kuga Y. 2012. Imaging through random multiple scattering media using integration of propagation and array signal processing. Waves in Random and Complex Media, 22(1): 24-39
  16. 16.
    Ishimaru A, Zhang C and Kuga Y. 2014. Hard wall imaging of objects hidden by non-penetrating obstacles using modified time reversal technique. IEEE Transactions on Antennas and Propagation, 62(7): 3645-3651
  17. 17.
    Ishimaru A. 2017. Electromagnetic Wave Propagation, Radiation, and Scattering: From Fundamentals to Applications. 2nd ed. Hoboken: Wiley-IEEE Press
  18. 18.
    Lee J S and Pottier E. 2009. Polarimetric Radar Imaging: From Basics to Applications. Baton Rouge: CRC Press
  19. 19.
    Lev-Ari H and Devaney A J. 2000. The time-reversal technique re-interpreted: subspace-based signal processing for multi-static target location//Proceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop. Cambridge, MA, USA: IEEE: 509-513
  20. 20.
    Li W M, Li Z Y, Chen E X and Feng Q. 2014. Status and development of tomographic SAR for forest vertical structural parameters inversion. Journal of Remote Sensing, 18(4): 741-751
  21. 21.
    Li Z, Zhou J M, Tian B S and Guo M. 2009. Research progress on application methods of POLSAR and INSAR. Journal of Remote Sensing, 13(S1): 283-289
  22. 22.
    Ling F L, Li Z Y, Bai L N, Tian X, Chen E X and Yang Y T. 2011. Rice mapping using ALOS PALSAR dual polarization data. Journal of Remote Sensing, 15(6): 1221-1234
  23. 23.
    Moreira A, Prats-Iraola P, Younis M, Krieger G, Hajnsek I and Papathanassiou K P. 2013. A tutorial on synthetic aperture radar. IEEE Geoscience and Remote Sensing Magazine, 1(1): 6-43
  24. 24.
    Prada C and Fink M. 1994. Eigenmodes of the time reversal operator: a solution to selective focusing in multiple-target media. Wave Motion, 20(2): 151-163
  25. 25.
    Reigber A and Moreira A. 2000. First demonstration of airborne SAR tomography using multibaseline L-band data. IEEE Transactions on Geoscience and Remote Sensing, 38(5): 2142-2152
  26. 26.
    Tsang L, Kong J A and Shin R T. 1985. Theory of Microwave Remote Sensing. New York: Wiley-Interscience Press
  27. 27.
    Tsang L, Kong J A, Ding K H and Ao C O. 2001. Scattering of Electromagnetic Waves, Volume II: Numerical Simulations. New York: Wiley
  28. 28.
    Ulaby F T and Long D G. 2014. Microwave Radar and Radiometric Remote Sensing. Ann Arbor: University of Michigan Press
  29. 29.
    van Zyl J and Kim Y. 2011. Synthetic Aperture Radar Polarimetry. New York: Wiley
  30. 30.
    Wang C, Zhang H, Tang Y X, Zhang B, Wu F and Wu H A. 2009. Exploration and practice of synthetic aperture radar interferometry (InSAR) research. Journal of Remote Sensing, 13(S1): 226-236
  31. 31.
    Yavuz M E and Teixeira F L. 2005. A numerical study of time-reversed UWB electromagnetic waves in continuous random media. IEEE Antennas and Wireless Propagation Letters, 4: 43-46
  32. 32.
    Yavuz M E and Teixeira F L. 2008. Space-frequency ultrawideband time-reversal imaging. IEEE Transactions on Geoscience and Remote Sensing, 46(4): 1115-1124
  33. 33.
    Yousefnia M, Ebrahimzadeh A, Dehmollaian M and Madannejad A. 2018. A time-reversal imaging system for breast screening: theory and initial phantom results. IEEE Transactions on Biomedical Engineering, 65(11): 2542-2551
  34. 34.
    Yu L L, Lai T, Zhao Y J and Chen J H. 2013. Joint estimation scheme of spaceborne synthetic aperture radar imaging parameters. Journal of Remote Sensing, 17(5): 1206-1222

قراءة النص الكامل

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website