Proceedings of the 2013 the International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2013)

SAR Imaging for Ships in Rough Seas Based on Deconvolutive STFT Spectrogram Method

Authors
Yu Zhao, Beibei Yang, Jinping Sun, Yuan Zhang
Corresponding Author
Yu Zhao
Available Online August 2013.
DOI
10.2991/rsete.2013.163How to use a DOI?
Keywords
SAR imaging, deconvolutive short-time Fourier transform spectrogram, ship motion modeling
Abstract

There is multi-degree-of-freedom non-cooperation motion of ships in rough seas which makes the quality of the ships’ SAR images get poor. In this paper, the ship motion model was built based on the strip theory at first. Then, the quality of the ships’ SAR images which are in different sea states was analyzed using the Standard Chirp Scaling Algorithm (CSA). At last, we propose a new SAR imaging method which is based on Deconvolutive Short-Time Fourier Transform DSTFT Spectrogram. Through simulation, the validity of the proposed method to improve the quality of SAR imaging was verified.

Copyright
© 2013, 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 2013 the International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2013)
Series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
10.2991/rsete.2013.163
ISSN
1951-6851
DOI
10.2991/rsete.2013.163How to use a DOI?
Copyright
© 2013, 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  - Yu Zhao
AU  - Beibei Yang
AU  - Jinping Sun
AU  - Yuan Zhang
PY  - 2013/08
DA  - 2013/08
TI  - SAR Imaging for Ships in Rough Seas Based on Deconvolutive STFT Spectrogram Method
BT  - Proceedings of the 2013 the International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2013)
PB  - Atlantis Press
SP  - 671
EP  - 674
SN  - 1951-6851
UR  - https://doi.org/10.2991/rsete.2013.163
DO  - 10.2991/rsete.2013.163
ID  - Zhao2013/08
ER  -