@inproceedings{6c9d56d06dbb44569105dc445a931d92,
title = "Scattering center modelling based on compressed sensing principle from under-sampling scattering field data",
abstract = "It has been proved that scattering center modeling for narrow band signals can be achieved through the optimum image matching of time-frequency representation (TFR). In order to obtain TFR, however, the azimuth sampling interval should be quite small for electrically large target, which results in a huge amount of electromagnetic computation. Under the situation of under-sampling scattered waves, aliasing distortions of the Doppler curves of scattering centers will be caused in TFR, which makes it hard to estimate the parameters of corresponding scattering centers from TFR. To deal with this problem, an approach for scattering center modelling from under-sampling scattered waves are presented in this paper. The random under-sampling scattered waves based on the principle of compressive sensing are applied to acquire the non-aliasing Doppler curves of scattering centers in TFR. The feasibility of this method has been validated by the simulation results.",
keywords = "compressive sensing, scattering center, time-frequency representation",
author = "Li, {Qi Feng} and Guo, {Kun Yi} and Bo Tang and Sheng, {Xin Qing}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = nov,
day = "1",
doi = "10.1109/IGARSS.2016.7729690",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2672--2675",
booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings",
address = "United States",
}