Skip to main content
Log in

Potential performance of polarimetric reference function of SAR data processing by coherent target decomposition

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

Significant employment of polarimetric synthetic aperture radar (SAR) is the classification of the Earth’s surface, which includes several processing algorithms, labelling, and representation options. This paper investigated the potential performance of the polarimetric reference function in SAR data processing to apply in coherent decomposition. The proposed methodology employed the simulated radar cross section of dihedral and trihedral corner reflector under a SAR geometry using physical optics (PO) and geometrical optics (GO) to produce the polarimetric reference function for azimuth compression in the processing of SAR data. The Pauli and the Krogager decompositions processed the compressed SAR data to investigate the effect and performance of the polarimetric reference function. The colour clustering results based on k-mean clustering algorithm could deliver more related scattering characteristic. The image pixel classification was strongly associated with the polarimetric reference function in processing step. These findings indicated that the obtained decomposition and clustering results could provide a better performance in visual impact and quantitative evaluation according to the decomposition term, as well as its physical interpretation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Curlander, J.C., McDonough, R.N.: Synthetic Aperture Radar: Systems and Signal Processing. Wiley, New York (1991)

    MATH  Google Scholar 

  2. Klausing, H., Holpp, W.: Radar mit realer und synthetischer Apertur: Konzeption und Realisierung. Oldenburg Verlag, Wien (2000)

    Book  Google Scholar 

  3. Evans, D.L., Farr, T.G., van Zyl, J.J., Zebker, H.A.: Radar polarimetry: analysis tools and applications. IEEE Geosci. Remote Sens. Lett. 26(6), 774–789 (1988)

    Article  Google Scholar 

  4. Huynen, J.R.: Phenomenological Theory of Radar Targets. Drukkerij Bronder-offset, Rotterdam (1970)

    Google Scholar 

  5. Holm, W.A., Barnes, R.M.: On Radar Polarization Mixed State Decomposition Theorems. In: Proceedings of 1988 USA National Radar Conference 249–254 (1988)

  6. Yang, J., Peng, Y.N., Yamaguchi, Y., Yamada, H.: On Huynen’s decomposition of a Kennaugh matrix. IEEE Geosci. Remote Sens. Lett. 3(3), 369–372 (2006)

    Article  Google Scholar 

  7. Freeman, A., Durden, S.L.: A three-component scattering model for polarimetric SAR data. IEEE Trans. Geosci. Remote Sens. 36(3), 963–973 (1998)

    Article  Google Scholar 

  8. Yamaguchi, Y., Moriyama, T., Ishido, M., Yamada, H.: Four-component scattering model for polarimetric SAR image decomposition. IEEE Trans. Geosci. Remote Sens. 43(8), 1699–1706 (2005)

    Article  Google Scholar 

  9. Cloude, S.R., Pottier, E.: A review of target decomposition theorems in radar polarimetry. IEEE Trans. Geosci. Remote Sens. 34(2), 498–518 (1996)

    Article  Google Scholar 

  10. van Zyl, J.J.: Unsupervised classification of scattering behavior using radar polarimetry data. IEEE Geosci. Remote Sens. Lett. 27(1), 36–45 (1989)

    Article  Google Scholar 

  11. Lee, J.S., Pottier, E.: Polarimetric Radar Imaging: From Basics to Applications. CRC Press, Boca Raton, FL, USA (2009)

    Book  Google Scholar 

  12. Krogager, E.: New decomposition of the radar target scattering matrix. Electron. Lett. 26(18), 1525–1527 (1990)

    Article  Google Scholar 

  13. Chunhua, L., Wang, J., Shang, J., Huang, X., Liu, J., Huffman, T.: Sensitivity study of Radarsat-2 polarimetric SAR to crop height and fractional vegetation cover of corn and wheat. Int. J. Remote Sens. 39(5), 1475–1490 (2018)

    Article  Google Scholar 

  14. Ren, B., Hou, B., Wen, Z., Xie, W., Jiao, L.: PolSAR image classification via multimodal sparse representation-based feature fusion. Int. J. Remote Sens. 39(22), 7861–7880 (2018)

    Article  Google Scholar 

  15. Eini-Zinab, S., Maghsoudi, Y., Sayedain, S.A.: Assessing the performance of indicators resulting from three-component Freeman-Durden polarimetric SAR interferometry decomposition at P-and L-band in estimating tropical forest aboveground biomass. Int. J. Remote Sens. 41(2), 433–454 (2020)

    Article  Google Scholar 

  16. Alberga, V., Krogager, E., Chandra, M., Wanielik, G.: Potential of coherent decompositions in SAR polarimetry and interferometry. In: Proceedings of 2004 IEEE International Geoscience and Remote Sensing Symposium (2004)

  17. Noori S.S., Tahmoresnezhad, J.: Joint Distinct Subspace Learning and Unsupervised Transfer Classification for Visual Domain Adaptation. Signal, Image and Video Processing (2020)

  18. Ma, J., Wan, H., Wang, J., Xia, H., Bai, C.: An Improved Scheme of Deep Dilated Feature Extraction on Pedestrian Detection. Signal, Image and Video Processing (2020)

  19. Phruksahiran, N., Michanan, J., Petchatree, S., Chandra, M.: Improving SAR data processing with polarimetric reference functions in the range Doppler algorithm. Int. J. Remote Sens. 38(23), 6582–6598 (2017)

    Article  Google Scholar 

  20. Horn, H.: The DLR airborne SAR project E-SAR. In: Proceedings of 1966 International Geoscience and Remote Sensing Symposium 249–254

  21. Cumming, L.G., Wong, F.H.: Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation. Artech House, Boston (2005)

    Google Scholar 

  22. Balanis, C.A.: Advanced Engineering Electromagnetics. Wiley, New York (1989)

    Google Scholar 

  23. Dybdal, R.B.: Radar cross section measurements. Proceedings of IEEE 75(4), 498–516 (1987)

    Article  Google Scholar 

  24. Phruksahiran, N., Chandra, M.: Polarimetric radar cross section under SAR geometry. Adv. Radio Sci. 11, 277–282 (2013)

    Article  Google Scholar 

  25. Griesser, T., Balanis, C.A.: Backscatter analysis of dihedral corner reflectors using physical optics and the physical theory of diffraction. IEEE Trans. Antennas Propag. 35(10), 1137–1147 (1987)

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Prof. Dr. Madhukar Chandra of TU Chemnitz, and Prof. Dr.-Ing. Alberto Moraira of DLR, Germany, for providing the E-SAR data set from the EU Project AMPER for use in the study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Narathep Phruksahiran.

Ethics declarations

Conflict of interest

No potential conflict of interest was reported by the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Phruksahiran, N. Potential performance of polarimetric reference function of SAR data processing by coherent target decomposition. SIViP 15, 1021–1029 (2021). https://doi.org/10.1007/s11760-020-01827-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-020-01827-9

Keywords

Navigation