On compressed sensing applied to 2-D SAR imaging

Peng Xiao, Ze Yu, Chunsheng Li, Yan Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Modern Synthetic Aperture Radar (SAR) systems operate with high bandwidths to achieve high resolution. But huge amount of data caused by high resolution and large swath can easily exceed the storage capacity and the transmittal bandwidth. Compressive Sensing (CS) techniques offer a framework for the detection and allocation of sparse signal with a reduced number of measurements. Under the framework of Compressive Sensing, sampling rate is not related to the effective bandwidth of signal, but determined by the content and structure of the interested information. Combining CS with SAR can settle the restraint relationship between the data quantity and resolution. Even better, for CS algorithm is a signal estimation method, CS-SAR may solve some problems which are brought by match filter method, such as sidelobe suppression, azimuth ambiguity elimination and super-resolution imaging.

Original languageEnglish
Title of host publicationConference Proceedings of 2013 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2013
Pages388-391
Number of pages4
Publication statusPublished - 2013
Externally publishedYes
Event2013 4th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2013 - Tsukuba, Japan
Duration: 23 Sept 201327 Sept 2013

Publication series

NameConference Proceedings of 2013 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2013

Conference

Conference2013 4th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2013
Country/TerritoryJapan
CityTsukuba
Period23/09/1327/09/13

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Xiao, P., Yu, Z., Li, C., & Wang, Y. (2013). On compressed sensing applied to 2-D SAR imaging. In Conference Proceedings of 2013 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2013 (pp. 388-391). Article 6705097 (Conference Proceedings of 2013 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2013).