@inproceedings{b0073727baf24b04893f302c805463cf,
title = "A novel RFI suppression method for compressive sensing SAR imaging",
abstract = "Synthetic Aperture Radar (SAR) has the all-day, all-weather ability to work. It has become one of the important sensors for military reconnaissance and civilian remote sensing. Radio frequency interference (RFI) is the major interference source for low frequency band SAR systems. This paper proposes a novel RFI suppression method for Compressive Sensing SAR. To the compressed sampled echo data, the greedy algorithm is adopted to estimate RFI spectrum with sparse feature, the minimum description length (MDL) criteria is used to estimate the RFI components sparsity. Then to the echo signal of each pulse, the RFI signal components are estimated and filtered in the time domain directly. Lastly, conventional compressive sensing SAR reconstruction algorithm can be applied to achieve imaging output.",
keywords = "Compressive Sensing, Greedy algorithm, MDL, RFI suppression, SAR",
author = "Chaoyun Mai and Ruxin Cui and Jinping Sun and Bingchen Zhang",
year = "2013",
language = "英语",
isbn = "9789078677772",
series = "International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2013",
publisher = "Atlantis Press",
pages = "597--600",
booktitle = "International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2013",
note = "2013 International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2013 ; Conference date: 26-07-2013 Through 28-07-2013",
}