You may have access to the free features available through My Research. You can save searches, save documents, create alerts and more. Please log in through your library or institution to check if you have access.
If you log in through your library or institution you might have access to this article in multiple languages.
Styles include MLA, APA, Chicago and many more. This feature may be available for free if you log in through your library or institution.
You may have access to it for free by logging in through your library or institution.
You may have access to different export options including Google Drive and Microsoft OneDrive and citation management tools like RefWorks and EasyBib. Try logging in through your library or institution to get access to these tools.
Alternate abstract:
Synthetic aperture radar (SAR) systems have the unique advantage of all-time and all-weather observation. In the past decade or so, with the continuous announcement of multi-mode, multi-angle, multi-dimension, wide-swath, high-resolution, and multi-static SAR observation technologies, SAR observation has been in the "new generation" stage. This paper first introduces the development of the observation capability of the new generation SAR, including how to realize the wide-swath, multi-temporal, and multi-level observation as well as moon-base observation; Then, the development and application of new information extraction methods such as the non-stationary statistical modeling, time-frequency decomposition, deep learning, and compressed sensing for new generation SAR images are summarized; Finally, recent application progress in urban management, vegetation mapping, polar region and ocean survey, and disaster monitoring are listed to promote wider and deeper applications of the new generation SAR.
