High resolution radar imaging from incomplete data

I. Erer*, S. Kent, M. Kartal

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

A new efficient method to obtain high resolution ISAR images in the case of missing observation data is presented. The available data segments are modeled by 2-D linear prediction of 2-D Cartesian frequency spectra using 2-D orthogonal lattice filters. Then the prediction models are used to estimate the missing data segments. It is shown that the IFT processing of the resulting data achieves better resolved images both in range and cross-range. Our algorithm is based on the 2-D prediction of the backscattered data, while other existing algorithms model range or cross-range profiles separately. Therefore, our method provides a better modeling for the gapped data.

Original languageEnglish
Title of host publication2008 IEEE Radar Conference, RADAR 2008
DOIs
Publication statusPublished - 2008
Event2008 IEEE Radar Conference, RADAR 2008 - Rome, Italy
Duration: 26 May 200830 May 2008

Publication series

Name2008 IEEE Radar Conference, RADAR 2008

Conference

Conference2008 IEEE Radar Conference, RADAR 2008
Country/TerritoryItaly
CityRome
Period26/05/0830/05/08

Keywords

  • 2D AR modeling
  • 2D linear prediction
  • High resolution radar imaging

Fingerprint

Dive into the research topics of 'High resolution radar imaging from incomplete data'. Together they form a unique fingerprint.

Cite this