Fractal feature based radar signal classification

A. K. Mishra, H. Feng, B. Mulgrew

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

Abstract

Automatic target recognition (ATR) using radar, is a much researched area with a demand for better and more accurate classification algorithms. In the present work, the local fractal dimensions of a synthetic aperture radar image have been used as features to classify ground targets. The performance of the fractal feature based ATR algorithm was compared with that of three other established ATR algorithms, viz. the simple yet powerful template matching ATR algorithm, the Gaussian model based Bayesian classifier, and the recently proposed principal component analysis based nearest neighbour algorithm. The fractal feature based classifier was shown to outperform all the other algorithms.

Original languageEnglish
Title of host publicationRADAR 2007 - The Institution of Engineering and Technology International Conference on Radar Systems
Number of pages4
Edition530 CP
DOIs
Publication statusPublished - 2007
Externally publishedYes
EventRADAR 2007 - The Institution of Engineering and Technology International Conference on Radar Systems - Edinburgh, United Kingdom of Great Britain and Northern Ireland
Duration: 15 Oct 200718 Oct 2007

Publication series

NameIET Conference Publications
Number530 CP

Conference

ConferenceRADAR 2007 - The Institution of Engineering and Technology International Conference on Radar Systems
Country/TerritoryUnited Kingdom of Great Britain and Northern Ireland
CityEdinburgh
Period15 Oct 200718 Oct 2007

Keywords

  • Automatic target recognition
  • Fractal dimension
  • Synthetic aperture radar

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