Skip to main content
Log in

Multichannel DEM reconstruction method based on Markov random fields for bistatic SAR

基于马尔可夫随机场 (Markov Random Field) 的双基 SAR 多通道 DEM 重建方法

  • Research Paper
  • Special Focus on Bistatic Synthetic Aperture Radar Signal Processing
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

It appears very interesting and particularly useful to perform DEM reconstruction with the configuration of multichannel bistatic SAR (BiSAR) because of its considerable advantages. In typical processing flow of multichannel interferometric synthetic aperture radar (InSAR), techniques based on statistical methods or iterative methods does not work very well with limits of specific BiSAR configurations. Moreover, the tradeoff between the correctness and precision of the reconstruction of different baselines needs to be overcome as well. Based on the advantages of multichannel BiSAR configuration, basic idea is the joint utilization of amplitude data, iterative reconstruction results and ML results to help the optimization of the total MRF energy function. Thus, a multichannel DEM reconstruction method based on Markov Random Fields (MRFs) for BiSAR, which concerns much about discontinuities and energy functions, is proposed to achieve not only correct but also more precise results. Afterward, the strategy to determine the weight parameter and processing flow is presented. Finally, simulated and real data experiments are given to validate the proposed method.

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

Similar content being viewed by others

References

  1. Loffeld O, Nies H, Peters V, et al. Models and useful relations for bistatic SAR processing. IEEE Trans Geosci Remote Sens, 2004, 42: 2031–2038

    Article  Google Scholar 

  2. Krieger G, Moreira A, Spaceborne bi- and multistatic SAR: potential and challenges. IEE Proc-Radar Sonar Navig, 2006, 153: 184–198

    Article  Google Scholar 

  3. Nies H, Behner F, Reuter S, et al. Polarimetric and interferometric applications in a bistatic hybrid SAR mode using Terrasar-X. In: Proceedings of Geoscience and Remote Sensing Symposium (IGARSS), Hawaii, 2010. 110–113

    Google Scholar 

  4. Duque S, López-Dekker P, Merlano J C, et al. Bistatic SAR along track interferometry with multiple fixed receivers. In: Proceedings of Geoscience and Remote Sensing Symposium (IGARSS), Hawaii, 2010. 4099–4102

    Google Scholar 

  5. Duque S, López-Dekker P, Mallorqui J J, et al. Experimental results with bistatic SAR tomography. In: Proceedings of Geoscience and Remote Sensing Symposium (IGARSS), Cape TOWN, 2009. II-37-II-40

    Google Scholar 

  6. Wang R, Deng Y, Zhang Z, et al. Double-channel bistatic SAR system with spaceborne illuminator for 2-D and 3-D SAR remote sensing. IEEE Trans Geosci Remote Sens, 2013, 51: 4496–4507

    Article  Google Scholar 

  7. Walterscheid I, Espeter T, Brenner A R, et al. Bistatic SAR experiments with PAMIR and TerraSAR-X-setup, processing, and image results. IEEE Trans Geosci Remote Sens, 2010, 48: 3268–3279

    Article  Google Scholar 

  8. Bamler R, Hartl P. Synthetic aperture radar interferometry. Inverse Probl, 1998, 14: R1–R54

    Article  MATH  MathSciNet  Google Scholar 

  9. Ghiglia D C, Pritt M D. Two-dimensional Phase Unwrapping: Theory, Algorithms, and Software. New York: Wiley, 1998

    MATH  Google Scholar 

  10. Ferraiuolo G, Meglio F, Pascazio V, et al. DEM reconstruction accuracy in multichannel SAR interferometry. IEEE Trans Geosci Remote Sens, 2009, 47: 191–201

    Article  Google Scholar 

  11. Pascazio V, Schirinzi G. Estimation of terrain elevation by multifrequency interferometric wide band SAR data. IEEE Signal Process Lett, 2001, 8: 7–9

    Article  Google Scholar 

  12. Ferretti A, Prati C, Rocca F. Multibaseline InSAR DEM reconstruction: the wavelet approach. IEEE Trans Geosci Remote Sens, 1999, 37: 705–715

    Article  Google Scholar 

  13. Thompson D G, Robertson A E, Arnold D V, et al. Multi-baseline interferometric SAR for iterative height estimation. In: Proceedings of Geoscience and Remote Sensing Symposium (IGARSS), Hamburg, 1999. 251–253

    Google Scholar 

  14. Pascazio V, Schirinzi G. Multifrequency InSAR height reconstruction through maximum likelihood estimation of local planes parameters. IEEE Trans Image Process, 2002, 11: 1478–1489

    Article  Google Scholar 

  15. Fornaro G, Monti Guarnieri A, Pauciullo A, et al. Maximum likelihood multi-baseline SAR interferometry. IEE Proc-Radar Sonar Navig, 2006, 153: 279–288

    Article  Google Scholar 

  16. Ferraiuolo G, Pascazio V, Schirinzi G. Maximum a posteriori estimation of height profiles in InSAR imaging. IEEE Trans Geosci Remote Sens, 2004, 1: 66–70

    Article  Google Scholar 

  17. Eineder M, Adam N. A maximum-likelihood estimator to simultaneously unwrap, geocode, and fuse SAR interferograms from different viewing geometries into one digital elevation model. IEEE Trans Geosci Remote Sens, 2005, 43: 24–36

    Article  Google Scholar 

  18. Yuan Z H, Deng Y K, Li F. Multichannel InSAR DEM reconstruction through improved closed-form robust Chinese remainder theorem. IEEE Geosci Remote Sens Let, 2013, 10: 1314–1318

    Article  Google Scholar 

  19. Ferraioli G, Ferraiuolo G, Pascazio V. Phase-offset estimation in multichannel SAR interferometry. IEEE Geosci Remote Sens Lett, 2008, 5: 458–462

    Article  Google Scholar 

  20. Ferraioli G, Shabou A, Tupin F, et al. Multichannel phase unwrapping with graph-cuts. IEEE Geosci Remote Sens Lett, 2009, 6: 562–566

    Article  Google Scholar 

  21. Shabou A, Baselice F, Ferraioli G. Urban digital elevation model reconstruction using very high resolution multichannel InSAR data. IEEE Trans Geosci Remote Sens, 2012, 50: 4748–4758

    Article  Google Scholar 

  22. Chen R P, Yu W D, Wang R, et al. Integrated denoising and unwrapping of InSAR phase based on Markov random fields. IEEE Trans Geosci Remote Sens, 2013, 51: 4473–4485

    Article  Google Scholar 

  23. Denis L, Tupin L, Darbon J, et al. SAR image regularization with fast approximate discrete minimization. IEEE Trans Image Process, 2009, 18: 1588–1600

    Article  MathSciNet  Google Scholar 

  24. Shao Y, Wang R, Deng Y K, et al. Error analysis of bistatic SAR imaging and stereoscopy bistatic SAR. IEEE Trans Geosci Remote Sens, 2013, 51: 4518–4543

    Article  Google Scholar 

  25. Wang R, Loffeld O, Neo Y L, et al. Focusing bistatic SAR data in airborne/stationary configuration. IEEE Trans Geosci Remote Sens, 2010, 48: 452–465

    Article  Google Scholar 

  26. Wang R, Loffeld O, Nies H, et al. Frequency-domain bistatic SAR processing for spaceborne/airborne configuration. IEEE Trans Aero Elect Syst, 2010, 46: 1329–1345

    Article  Google Scholar 

  27. Li S Z. Markov Random Field Modeling in Image Analysis. New York: Springer-Verlag, 2009. 126–129

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Feng Hong.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hong, F., Tang, J. & Lu, P. Multichannel DEM reconstruction method based on Markov random fields for bistatic SAR. Sci. China Inf. Sci. 58, 1–14 (2015). https://doi.org/10.1007/s11432-015-5320-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-015-5320-z

Keywords

Navigation