ISAR imaging using filtered compressive sensing

Many methods have been developed over the last several decades to provide spatial imaging from backscattered ISAR data, including range-Doppler processing, subspace techniques, and more recently, compressive sensing. Range-Doppler processing generally has a lower resolution than subspace and compres...

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Bibliographic Details
Main Authors: Mitchell, Jon, Tjuatja, Saibun
Format: Conference Proceeding
Language:English
Subjects:
Compressed sensing
Filtering
Frequency measurement
Imaging
Signal to noise ratio
Spatial resolution
Online Access:Request full text
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Summary:Many methods have been developed over the last several decades to provide spatial imaging from backscattered ISAR data, including range-Doppler processing, subspace techniques, and more recently, compressive sensing. Range-Doppler processing generally has a lower resolution than subspace and compressive sensing techniques. Subspace techniques provide a high resolution image and perform well in the presence of noise, but require a sufficiently high measurement bandwidth. In addition, in the presence of significant noise, subspace dimensionality can be difficult to determine. Compressive sensing can provide a very high resolution image under ideal circumstances but generally performs poorly in the presence of noise. This paper proposes a filtered compressive sensing method that improves compressive sensing ISAR imaging over direct methods.
ISSN:2153-7003
DOI:10.1109/IGARSS.2017.8127476