A novel method of constructing measurement matrix for CS-based SAR imaging

Haili Li, Xia Bai*, Juan Zhao, Ran Tao

*Corresponding author for this work

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

Abstract

Compressed sensing (CS) is a recently developed theory which allows reconstruction of sparse signals with a number of measurements much lower than that required by the Nyquist sampling. The theory has been applied in many areas within synthetic aperture radar (SAR). This paper presents a novel method of constructing measurement matrix for CS-based SAR imaging, which enables the sensing matrix to meet RIP with high probability. Simulated results demonstrate the effectiveness of the proposed method, which can obtain a high quality radar image with fewer data samples, and the advantage of the proposed method is more obvious especially at high noise levels.

Original languageEnglish
Title of host publication2012 5th International Congress on Image and Signal Processing, CISP 2012
Pages1754-1758
Number of pages5
DOIs
Publication statusPublished - 2012
Event2012 5th International Congress on Image and Signal Processing, CISP 2012 - Chongqing, China
Duration: 16 Oct 201218 Oct 2012

Publication series

Name2012 5th International Congress on Image and Signal Processing, CISP 2012

Conference

Conference2012 5th International Congress on Image and Signal Processing, CISP 2012
Country/TerritoryChina
CityChongqing
Period16/10/1218/10/12

Keywords

  • SAR
  • compressed sensing
  • measurement matrix

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