References
- 1. Nicolas, J.-M., G. Vasile, M. Gay, F. Tupin, Em. Trouvé. SAR Processing in the Temporal Domain: Application to Direct Interferogram Generation and Mountain Glacier Monitoring Can. – J. Remote Sensing, Vol., 2007, No 1, pp. 52-59.
- 2. Leijen, V., F. R. Hanssen. Interferometric Radar Meteorology: Resolving the Acquisition Ambiguity. – In: CEOS SAR Workshop, Ulm Germany, 27-28 May 2004, pp. 6-14.
- 3. Colesanti, C., A. Ferretti, F. Novali, C. Prati, F. Rocca. SAR Monitoring of Progressive and Seasonal Ground Deformation Using the Permanent Scatterers Technique. – IEEE Transactions on Geoscience and Remote Sensing, Vol., July 2003, No 7, pp. 1685-1701.
- 4. Figueiredo, M. A. T., R. D. Nowak, S. J. Wright. Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems. – IEEE Journal of Selected Topics in Signal Processing, Vol., December 2007, No 4, pp. 586-597.
- 5. Tropp, J. Just Relax: Convex Programming Methods for Identifying Sparse Signals. – IEEE Transactions on Information Theory, Vol., 2006, pp. 1030-1051.
- 6. Kim, S.-J., K. Koh, M. Lustig, S. Boyd, D. Gorinevsky. An Interior-Point Method for Large-Scale-Regularized Least Squares. – IEEE Journal of Selected Topics in Signal Processing, Vol., 4 December 2007, pp. 606-617.
- 7. Donaho, D. L. Compressed Sensing. – IEEE Trans. on Inf. Theory, Vol., 2006, No 4, pp.1289-1306.
- 8. Hayashi, K., M. Nagahara, T. Tanaka. A User’s Guide to Compressed Sensing for Communication Systems. – IEICE Trans. on Communications, Vol., March 2013, No 3, pp. 685-712.
- 9. Gurbuza, A. C., J. H. McClellanb, W. R. Scott, B. Jr. Compressive Sensing for Subsurface Imaging Using Ground Penetrating Radar. – Signal Processing, Vol., October 2009, No 10, pp. 1959-1972.
- 10. Cai, J.-L., C.-M. Tong, W.-J. Zhong, W.-J. Ji. 3D Imaging Method for Stepped Frequency Ground Penetrating Radar Based on Compressive Sensing. – Progress in Electromagnetics Research M, Vol., 2012, pp. 153-165.
- 11. McClellan, C. J. H., W. R. Scott. A Compressive Sensing Data Acquisition and Imaging Method for Stepped-Frequency GPRs. – IEEE Transation on Signal Processing, Vol., July 2009, No 7, pp. 2640-2650.
- 12. Shastry, M. C., R. M. Narayanan, M. Rangaswamy. Analysis of the Tolerance of Compressive Noise Radar Systems to Multiplicative Perturbations. – In: Proc. of SPIE’9109, Compressive Sensing III, 910905, 23 May 2014.
- 13. Lin, Y. G., B. C. Zhang, W. Hong, Y. R. Wu. Along-Track Interferometric SAR Imaging Based on Distributed Compressed Sensing. – Electronics Letters, Vol., 10 June 2010, No 12, p. 858-860.
- 14. Yang, J., J. Thompson, X. Huang, T. Jin. Random-Frequency SAR Imaging Based on Compressed Sensing. – IEEE Trans. on Geoscience and Remote Sensing, Vol., February 2013, No 2, pp. 983-994.
- 15. Li, J., S. Zhang, J. Chang. Applications of Compressed Sensing for Multiple Transmitters Multiple Azimuth Beams SAR Imaging. – Progress in Electromagnetics Research, Vol., 2012, pp. 259-275.
- 16. Wei, S.-J., X.-L. Zhang, J. Shi. Linear Array SAR Imaging Via Compressed Sensing. – Progress in Electromagnetics Research, Vol., 2011, pp. 299-319.
- 17. Wei, S.-J., X.-L. Zhang, J. Shi, G. Xiang. Sparse Reconstruction for SAR Imaging Based on Compressed Sensing. – Progress in Electromagnetics Research, Vol., 2010, pp. 63-81.
- 18. Qiu, W., E. Giusti, A. Bacci, M. Martorella, F. Berizzi et al. Compressive Sensing for Passive ISAR with DVB-T Signal. – In: Proc. of IRS-2013, 19-21 June 2013, pp. 113-118.
- 19. Kim, S., K. Koh, M. Lustig, S. Boyd, D. Gorinvesky. A Method for Large-Scale ℓ-Regularized Least Squares Problems with Applications in Signal Processing and Statistics. Tech. Report, Dept. of Electrical Engineering, Stanford University, 2007.
DOI: https://doi.org/10.1515/cait-2015-0091 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702 (formerly 1314-4081)
Language: English
Page range: 77 - 87
Published on: Jan 19, 2016
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
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© 2016 A. Lazarov, D. Minchev, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
