Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

The Method of SAR RFI Suppression Based on Compressed Sensing

Authors
Shuya Kong, Wei Ye, Guochao Lao, Weikun Zhang
Corresponding Author
Shuya Kong
Available Online March 2016.
DOI
10.2991/icmmct-16.2016.142How to use a DOI?
Keywords
Compress Sensing, Synthetic Aperture Radar, RFI Suppression, Minimum Description Length
Abstract

To the synthetic aperture radar (SAR) imaging system which using Compressed Sensing (CS) technique, radio frequency interference (RFI) would undermine the priori sparse condition and cause deterioration of image quality. In this paper, under the condition of the sparse target scene, it builds the target echo signal and RFI redundant dictionary, according to RFI sparse features on their redundant dictionary, greedy algorithm was used in conjunction with the minimum description length (MDL) criterion to estimate the sparseness of RFI, and SAR imaging RFI suppression algorithms on the compressed domain was designed based on this basis. Simulation results show that in the larger JSR conditions the algorithm can effectively suppress SAR radio interference and achieve better imaging results.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
978-94-6252-165-0
ISSN
2352-5401
DOI
10.2991/icmmct-16.2016.142How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Shuya Kong
AU  - Wei Ye
AU  - Guochao Lao
AU  - Weikun Zhang
PY  - 2016/03
DA  - 2016/03
TI  - The Method of SAR RFI Suppression Based on Compressed Sensing
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 733
EP  - 738
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.142
DO  - 10.2991/icmmct-16.2016.142
ID  - Kong2016/03
ER  -