TY - GEN
T1 - Range-Doppler processing via fourier coefficients
T2 - 2016 IEEE Radar Conference, RadarConf 2016
AU - Aberman, Kfir
AU - Eldar, Yonina C.
N1 - Publisher Copyright: © 2016 IEEE.
PY - 2016/6/3
Y1 - 2016/6/3
N2 - The increasing demand for wide swath, high-resolution, Synthetic Aperture Radar (SAR) images, requires high sampling rates which are difficult to attain in practice. Consequently, sampling rate reduction is of high practical value in radar imaging. In this paper, we introduce a new algorithm, equivalent to the well-known Range-Doppler method, to process SAR data using the Fourier coefficients of the raw signals. We then demonstrate how to exploit the new algorithm features, particularly, the relationship between the processed signals before and after Range Cells Migration Correction (RCMC), to reduce sampling rate at the acquisition stage and process the signals effectively at sub-Nyquist rates. Beyond sampling rate reduction, the proposed fast recovery algorithm forms a new CS-SAR imaging method that can be applied to high-quality and high-resolution real SAR imaging data acquired at sub-Nyquist rates. The performance of the algorithms is assessed using simulated data sets.
AB - The increasing demand for wide swath, high-resolution, Synthetic Aperture Radar (SAR) images, requires high sampling rates which are difficult to attain in practice. Consequently, sampling rate reduction is of high practical value in radar imaging. In this paper, we introduce a new algorithm, equivalent to the well-known Range-Doppler method, to process SAR data using the Fourier coefficients of the raw signals. We then demonstrate how to exploit the new algorithm features, particularly, the relationship between the processed signals before and after Range Cells Migration Correction (RCMC), to reduce sampling rate at the acquisition stage and process the signals effectively at sub-Nyquist rates. Beyond sampling rate reduction, the proposed fast recovery algorithm forms a new CS-SAR imaging method that can be applied to high-quality and high-resolution real SAR imaging data acquired at sub-Nyquist rates. The performance of the algorithms is assessed using simulated data sets.
KW - compressed sensing
KW - sparse recovery
KW - sub-Nyquist sampling
KW - synthetic aperture radar (SAR)
UR - http://www.scopus.com/inward/record.url?scp=84978221143&partnerID=8YFLogxK
U2 - 10.1109/RADAR.2016.7485295
DO - 10.1109/RADAR.2016.7485295
M3 - منشور من مؤتمر
T3 - 2016 IEEE Radar Conference, RadarConf 2016
SP - 1201
EP - 1205
BT - 2016 IEEE Radar Conference, RadarConf 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 2 May 2016 through 6 May 2016
ER -