A robust and efficient SAR ATR algorithm using a hybrid model of fractional fourier transform and pulse coupled neural network

Santu Sardar, Amit K. Mishra

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

Abstract

A hybrid framework consisting of Fractional Fourier Transform (FrFT) and Pulse coupled Neural network (PCNN) is proposed in this paper for highly accurate and orientation, position & scale invariant synthetic aperture radar (SAR) automatic target recognition (ATR). FrFT is used to gather scattering information and insights that are attainable using time-frequency and time-scale techniques, whereas PCNN is used to achieve invariant target recognition. Public release of the MSTAR dataset is used to validate the proposed system. We compared our proposed system performance with existing approaches and established the better performance of this system. We have shown that, even with reduced training sets, the proposed system shows consistent performance whereas the performance of conventional systems degrades.

Original languageEnglish
Title of host publicationIEEE MTT-S International Microwave and RF Conference 2014, IMaRC 2014 - Collocated with Intemational Symposium on Microwaves, ISM 2014
PublisherIEEE Press
Pages121-124
Number of pages4
ISBN (Electronic)978-1-4799-6317-1
DOIs
Publication statusPublished - 15 Dec 2014
Externally publishedYes
Event2014 IEEE International Microwave and RF Conference, IMaRC 2014 - Banglore, India
Duration: 15 Dec 201417 Dec 2014

Publication series

NameIEEE MTT-S International Microwave and RF Conference 2014, IMaRC 2014 - Collocated with Intemational Symposium on Microwaves, ISM 2014

Conference

Conference2014 IEEE International Microwave and RF Conference, IMaRC 2014
Country/TerritoryIndia
CityBanglore
Period15 Dec 201417 Dec 2014

Keywords

  • ATR
  • FrFT
  • MSTAR
  • PCNN
  • SAR

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