On the use of least-squares lattice structures for missing data in ISAR imaging

S. Çopuroǧlu*, Ö Gültekin, I. Erer

*Corresponding author for this work

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

Abstract

In this work, we consider the spectral estimation of the gapped data encountered in inverse synthetic aperture radar (ISAR) imaging. For the estimation of missing data, we propose the use of Least-Square Lattice (LSL) Filters. The proposed method consists of interpolating the rows of two-dimensional backscattered data, where each row corresponds to the backscattered target data from a specific aspect angle. IFFT processing yields the enhanced spectral estimate of interpolated data. To demonstrate the effectiveness of the proposed algorithm, numerical results based on simulated data are presented.

Original languageEnglish
Title of host publicationRAST 2009 - Proceedings of 4th International Conference on Recent Advances Space Technologies
Pages447-452
Number of pages6
DOIs
Publication statusPublished - 2009
Event4th International Conference on Recent Advances in Space Technologies 2009, RAST '09 - Istanbul, Turkey
Duration: 11 Jun 200913 Jun 2009

Publication series

NameRAST 2009 - Proceedings of 4th International Conference on Recent Advances Space Technologies

Conference

Conference4th International Conference on Recent Advances in Space Technologies 2009, RAST '09
Country/TerritoryTurkey
CityIstanbul
Period11/06/0913/06/09

Keywords

  • Component
  • ISAR imaging
  • Least-squares lattice structure
  • Missing data

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