@inproceedings{2c6fa8cfb6924b6082f8df581b805a7f,
title = "SAR imaging from randomly sampled phase history using compressive sensing",
abstract = "Reconstructing synthetic aperture Radar (SAR) images from gapped phase history or k space data, is a major problem for SAR engineers. In this work we use the newly proposed compressive sensing (CS) algorithms to form SAR images of randomly and sparsely sampled k space data. We also investigate the effect of adding phase noise of various degrees of severity in the sparse and random k space data. We show that CS based algorithms can intelligibly reconstruct SAR images from randomly sparse phase history data and can tolerate a good amount of phase noise corruption. Dantzig selector based CS algorithm was found to perform better than the usual l 1 norm based CS algorithm.",
author = "Mishra, \{Amit Kumar\} and Rohan Phogat and Shikhar Mann",
year = "2012",
month = may,
day = "23",
doi = "10.1109/IRS.2012.6233319",
language = "English",
isbn = "978-1-4577-1838-0",
series = "Proceedings International Radar Symposium",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "221--224",
booktitle = "2012 13th International Radar Symposium, IRS-2012",
address = "United States of America",
note = "2012 13th International Radar Symposium, IRS-2012 ; Conference date: 23-05-2012 Through 25-05-2012",
}