×

Matrix completion-based distributed compressive sensing for polarimetric SAR tomography. (English) Zbl 1497.94017

MSC:

94A12 Signal theory (characterization, reconstruction, filtering, etc.)
Full Text: DOI

References:

[1] Zhu X, Bamler R. Tomographic SAR inversion by L1-norm regularization-the compressive sensing approach. IEEE Trans Geosci Remote Sens, 2010, 48: 3839-3846 · doi:10.1109/TGRS.2010.2048117
[2] Donoho D. Compressed sensing. IEEE Trans Inf Theory, 2006, 52: 1289-1306 · Zbl 1288.94016 · doi:10.1109/TIT.2006.871582
[3] Zhang B C, Hong W, Wu Y R. Sparse microwave imaging: principles and applications. Sci China Inf Sci, 2012, 55: 1722-1754 · Zbl 1270.94026 · doi:10.1007/s11432-012-4633-4
[4] Duarte, F.; Sarvotham, S.; Baron, D.; etal., Distributed compressed sensing of jointly sparse signals, 1537-1541 (2005)
[5] Aguilera E, Nannini M, Reigber A. Multisignal compressed sensing for polarimetric SAR tomography. IEEE Geosci Remote Sens Lett, 2012, 9: 871-875 · doi:10.1109/LGRS.2012.2185482
[6] Candès E, Recht B. Exact matrix completion via convex optimization. Found Comput Math, 2009, 9: 717-772 · Zbl 1219.90124 · doi:10.1007/s10208-009-9045-5
[7] Bi H, Jiang C, Zhang B, et al. Radar change imaging with undersampled data based on matrix completion and bayesian compressive sensing. IEEE Geosci Remote Sens Lett, 2015, 12: 1546-1550 · doi:10.1109/LGRS.2015.2412677
[8] Hajnsek I, Scheiber R, Ulander L, et al. BioSAR 2007 Technical Assistance for the Development of Airborne SAR and Geophysical Measurements During the BioSAR 2007 Experiment: Final Report without Synthesis. European Space Agency Technical Report 20755/07/nl/cb, 2008
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.