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PIER PIER B PIER C PIER M PIER Letters PIER Photonics
2015-02-21
Resolution Enhancement for LASAR 3D Imaging via ℓ1 Regularization and SVA
By
Gao Xiang,

    Dr. Gao Xiang

    School of Electronic Engineering

    University of Electronic Science and Technology of China

    China

    Homepage

Xiaoling Zhang,

    Dr. Xiaoling Zhang

    School of Electronic Engineering

    University of Electronic Science and Technology of China

    China

    Homepage

Jun Shi,

    Dr. Jun Shi

    School of Electronic Engineering

    University of Electronic Science and Technology of China

    China

    Homepage

Shun-Jun Wei

    Dr. Shun-Jun Wei

    School of Electronic Engineering

    University of Electronic Science and Technology of China

    China

    Homepage

Progress In Electromagnetics Research M, Vol. 41, 95-104, 2015
doi:10.2528/PIERM14121901 | Google Scholar

Abstract
Linear array SAR (LASAR) has been attracting more and more attention for its capability of obtaining three dimensional (3D) resolutions. However, the low resolution in cross track (CT) direction limited by the length of its linear antenna array has become the bottleneck of its practical applications. To overcome this problem, we present a novel algorithm based on sparse reconstruction (SR) to improve the resolution in CT direction. First, it establishes a 1D real-valued sparse model for LASAR, which deals with the 3D image column by column along CT direction in each equi-range slice. This enables it to handle large scenes. Second, it employs the spatially variant apodization (SVA) to filter bases of the measurement matrix. As a result, the cross coherence gets suppressed as well, and it is helpful to improve the performance of sparse reconstruction algorithms (SRAs). Third, we propose the resolution enhancement ability (REA), which provides a new idea to evaluate how many times the resolution could be improved. Experimental results validate that when the signal to noise ratio (SNR) is 30 dB, LASAR could usually obtain 2 times of resolution improvement in CT direction, while the proposed method further improves the REA by a factor about 2.5. Moreover, the 3D surface terrain simulation shows a great improvement for the digital elevation map (DEM) in resolution enhancement.
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Citation
Gao Xiang, Xiaoling Zhang, Jun Shi, and Shun-Jun Wei, "Resolution Enhancement for LASAR 3D Imaging via ℓ1 Regularization and SVA," Progress In Electromagnetics Research M, Vol. 41, 95-104, 2015.
doi:10.2528/PIERM14121901
References

1. Klare, J., A. Brenner, and J. Ender, "A new airborne radar for 3D imaging - image formation using the ARTINO principle," EUSAR, Dresden, Germany, 2006.        Google Scholar

2. Marechal, N., "Tomographic formulation of interferometric SAR for terrain elevation mapping," IEEE Transactions on Geoscience and Remote Sensing, Vol. 33, No. 3, 726-739, 1995.
doi:10.1109/36.387588        Google Scholar

3. Eineder, M., N. Adam, R. Bamler, et al. "Spaceborne spotlight SAR interferometry with TerraSAR-X," IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, No. 5, 1524-1535, 2009.
doi:10.1109/TGRS.2008.2004714        Google Scholar

4. Mahafza, B. R. and M. Sajjadi, "Three-dimensional SAR imaging using linear array in transverse motion," IEEE Transactions on Aerospace and Electronic Systems, Vol. 32, No. 1, 499-510, 1996.
doi:10.1109/7.481296        Google Scholar

5. Chan, T.-K., Y. Kuga, and A. Ishimaru, "Experimental studies on circular SAR imaging in clutter using angular correlation function technique," IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, No. 5, 2192-2197, 1999.
doi:10.1109/36.789616        Google Scholar

6. Axelsson, S. R. J., "Mapping performance of curved-path SAR," IEEE Transactions on Geoscience and Remote Sensing, Vol. 40, No. 10, 2224-2228, 2002.
doi:10.1109/TGRS.2002.803740        Google Scholar

7. Axelsson, S. R. J., "Beam characteristics of three-dimensional SAR in curved or random paths," IEEE Transactions on Geoscience and Remote Sensing, Vol. 42, No. 10, 2324-2334, 2004.
doi:10.1109/TGRS.2004.834802        Google Scholar

8. Ishimaru, A., T.-K. Chan, and Y. Kuga, "An imaging technique using confocal circular synthetic aperture radar," IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, No. 5, 1524-1530, 1998.
doi:10.1109/36.718856        Google Scholar

9. Weib, M. and J. H. G. Ender, "A 3D imaging radar for small unmanned airplanes - ARTINO," European Radar Conference (EURAD), 209-212, 2005.        Google Scholar

10. Shi, J., X. L. Zhang, J. Y. Yang, et al. "Experiment results on one-active LASAR," IEEE Radar Conference, 1-4, Pasadena, CA, 2009.        Google Scholar

11. Xiang, G., X. L. Zhang, and J. Shi, "Airborne 3-D forward looking SAR imaging via chirp scaling algorithm," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 3011-3014, 2011.        Google Scholar

12. Ren, X. Z., J. T. Sun, and R. L. Yang, "A new three-dimensional imaging algorithm for airborne forward-looking SAR," IEEE Geoscience and Remote Sensing Letters, Vol. 8, No. 1, 153-157, 2011.
doi:10.1109/LGRS.2010.2055035        Google Scholar

13. López-Dekker, P. and J. J. Mallorquí, "Capon- and APES- based SAR processing: Performance and practical considerations," IEEE Transactions on Geoscience and Remote Sensing, Vol. 48, No. 5, 2388-2402, 2010.
doi:10.1109/TGRS.2009.2038902        Google Scholar

14. Xu, X. J. and R. M. Narayanan, "Enhanced resolution in SAR/ISAR imaging using iterative sidelobe apodization," IEEE Transactions on Image Processing, Vol. 14, No. 4, 537-547, 2005.
doi:10.1109/TIP.2004.841198        Google Scholar

15. Lim, B. G., J. C. Woo, and Y. S. Kim, "Noniterative super-resolution technique combining SVA with modified geometric mean filter," IEEE Geoscience and Remote Sensing Letters, Vol. 7, No. 4, 713-717, 2010.
doi:10.1109/LGRS.2010.2046877        Google Scholar

16. Bruckstein, A., D. Donoho, and M. Elad, "From sparse solutions of systems of equations to sparse modeling of signals and images," Siam Review, Vol. 51, No. 1, 34-81, 2009.
doi:10.1137/060657704        Google Scholar

17. Potter, L. C., E. Ertin, J. T. Parker, et al. "Sparsity and compressed sensing in radar imaging," Proceedings of the IEEE, Vol. 98, No. 6, 1006-1020, 2010.
doi:10.1109/JPROC.2009.2037526        Google Scholar

18. Zhu, X. X. and R. Bamler, "Super-resolution power and robustness of compressive sensing for spectral estimation with application to spaceborne tomographic SAR," IEEE Transactions on Geoscience and Remote Sensing, Vol. 50, No. 1, 247-258, 2012.
doi:10.1109/TGRS.2011.2160183        Google Scholar

19. Wei, S. J. and X. L. Zhang, "Linear array SAR imaging via compressed sensing," Progress In Electromagnetics Research, Vol. 117, 299-319, 2011.
doi:10.2528/PIER11033105        Google Scholar

20. Shi, J., X. L. Zhang, G. Xiang, et al. "Signal processing for microwave array imaging: TDC and sparse recovery," IEEE Transactions on Geoscience and Remote Sensing, Vol. 50, No. 11, 4584-4598, 2012.
doi:10.1109/TGRS.2012.2191293        Google Scholar

21. Wei, S. J. and X. L. Zhang, "Linear array SAR 3-D imaging based on compressed sensing," Journal of Astronautics, Vol. 32, No. 11, 2403-2409, 2011.        Google Scholar

22. Smith, B. H., "Generalization of spatially variant apodization to noninteger Nyquist sampling rates," IEEE Transactions on Image Processing, Vol. 9, No. 6, 1088-1093, 2000.
doi:10.1109/83.846250        Google Scholar

23. Shi, J., X. L. Zhang, J. Y. Yang, et al. "Radix-N resolution-fusion for LASAR via orthogonal complement decomposition," IEEE Geoscience and Remote Sensing Letters, Vol. 6, No. 1, 147-151, 2009.
doi:10.1109/LGRS.2008.2009951        Google Scholar

24. Batu, O. and M. Cetin, "Parameter selection in sparsity-driven SAR imaging," IEEE Transactions on Aerospace and Electronic Systems, Vol. 47, No. 4, 3040-3050, 2011.
doi:10.1109/TAES.2011.6034687        Google Scholar

25. Stodden, V., L. Carlin, D. Donoho, et al. "SparseLab,", URL http://sparselab.stanford.edu/, 2013.        Google Scholar

26. Tsaig, Y. and D. L. Donoho, "Extensions of compressed sensing," Signal Processing, Vol. 86, No. 3, 549-571, 2006.
doi:10.1016/j.sigpro.2005.05.029        Google Scholar

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