Compressed Sensing Radar Imaging With Compensation of Observation Position Error

Jungang Yang*, Xiaotao Huang, John Thompson, Tian Jin, Zhimin Zhou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Compressed sensing (CS) based radar imaging requires the use of a mathematical model of the observation process. Inaccuracies in the observation model may cause defocusing in the reconstructed images. In the observation process, the observation positions are usually not known perfectly. Imperfect knowledge of the observation positions is a major source of model errors in imaging. In this paper, a method is proposed to compensate the observation position errors in CS-based radar imaging. Instead of treating the observation-position-induced model errors as phase errors in the data, the proposed method can determine the observation position errors as part of the imaging process. It uses an iterative algorithm, which cycles through steps of target reconstruction and observation position error estimation and compensation. The proposed method can estimate the observation position errors accurately, and the reconstruction quality of the target images can be improved significantly. Simulation results and experimental results from rail-mounted radar and airborne synthetic aperture radar are presented to show the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)4608-4620
Number of pages13
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume52
Issue number8
DOIs
Publication statusPublished - Aug 2014

Keywords / Materials (for Non-textual outputs)

  • Autofocus
  • compressed sensing (CS)
  • observation position error
  • radar imaging
  • SYNTHETIC-APERTURE RADAR
  • SPARSE REPRESENTATION
  • SIGNAL RECOVERY
  • AIRBORNE SAR
  • REGULARIZATION
  • PURSUIT

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