Compressive sensing SAR range compression with chirp scaling principle

Compressive sensing （CS） techniques offer a framework for the detection and allocation of sparse signal with a reduced number of measurements. This paper proposes a novel SAR range compression, namely compressive sensing with chirp scaling （CS-CS）, achieving the same range resolution as conventional...

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Bibliographic Details
Published inScience China. Information sciences Vol. 55; no. 10; pp. 2292 - 2300
Main Authors Xiao, Peng, Yu, Ze, Li, ChunSheng
Format Journal Article
LanguageEnglish
Published Heidelberg SP Science China Press 01.10.2012
Springer Nature B.V
Subjects
Chirp
Compressing
Compression tests
Computer Science
Detection
Error analysis
Errors
Information Systems and Communication Service
Principles
Research Paper
Sampling
Scaling
Synthetic aperture radar
压缩
原理
啁啾
感知
测量信号
特区
线性调频
缩放
range cell migration correction
synthetic aperture radar
error
compressive sensing
radar signal processing
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Summary:Compressive sensing （CS） techniques offer a framework for the detection and allocation of sparse signal with a reduced number of measurements. This paper proposes a novel SAR range compression, namely compressive sensing with chirp scaling （CS-CS）, achieving the same range resolution as conventional SAR ap- proach, while using fewer range samplings. In order to realize accurate range cell migration correction （RCMC）, chirp scaling principle is used to construct reference matrix for compressive sensing recovery. Additionally, error diagrams are designed for measurement of the performance of CS-CS, and some experiments of using real data are performed to deal with the errors caused by three conditions： SNR, sparsity and sampling.
Bibliography:11-5847/TP
synthetic aperture radar, compressive sensing, range cell migration correction, error, radar signal processing
Compressive sensing （CS） techniques offer a framework for the detection and allocation of sparse signal with a reduced number of measurements. This paper proposes a novel SAR range compression, namely compressive sensing with chirp scaling （CS-CS）, achieving the same range resolution as conventional SAR ap- proach, while using fewer range samplings. In order to realize accurate range cell migration correction （RCMC）, chirp scaling principle is used to construct reference matrix for compressive sensing recovery. Additionally, error diagrams are designed for measurement of the performance of CS-CS, and some experiments of using real data are performed to deal with the errors caused by three conditions： SNR, sparsity and sampling.
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SourceType-Scholarly Journals-1
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content type line 23
ISSN:1674-733X
1869-1919
DOI:10.1007/s11432-012-4613-8