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Content Provider | IET Digital Library |
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Author | Yi, Liu Ding, Dazhi Chen, Rushan Tao, Shifei |
Abstract | Radar imaging of the ship is one of the important means for surveillance and reconnaissance of targets. Here, the K-distribution is used for the statistical characterisation of echo model in sea-clutter environment. FEKO software is used to simulate the ship model. The multi-radar data fusion technique and Sparse Bayesian learning algorithm are used to generate ISAR target images in the different levels of sea condition. The simulation results show that the multi-radar data fusion algorithm not only has a significant inhibitory effect on sea-clutter but also improves the radar image resolution. |
Starting Page | 6898 |
Ending Page | 6901 |
Page Count | 4 |
Volume Number | 2019 |
e-ISSN | 20513305 |
Issue Number | Issue 20, Oct (2019) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/20 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0367 |
Journal | The Journal of Engineering |
Publisher | The Institution of Engineering and Technology |
Publisher Date | 2019-07-11 |
Access Restriction | Open |
Rights License | Creative Commons Attribution-No Derivs License (http://creativecommons.org/licenses/by-nd/3.0/) |
Subject Keyword | Bayes Method Computer Vision And Image Processing Technique Echo Model FEKO Software High-resolution ISAR Imaging Image Fusion Image Resolution ISAR Target Image K-distribution Knowledge Engineering Technique Learning in AI Marine Radar Multiradar Data Fusion Algorithm Multiradar Data Fusion Technique Optical, Image And Video Signal Processing Radar Clutter Radar Equipment Radar Image Resolution Radar Imaging Radar Resolution Reconnaissance Sea Condition Sea-clutter Environment Ship Model Ships Sparse Bayesian Learning Algorithm Statistical Characterisation Statistics Surveillance Synthetic Aperture Radar System And Application Target Surveillance |
Content Type | Text |
Resource Type | Article |
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