Target range estimation in OFDM radar system via kernel least mean square technique

U. K. Singh, R. Mitra, V. Bhatia, A. K. Mishra

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

Abstract

Estimating range and velocity of a target is an integral part of radar systems. The orthogonal frequency division multiplex (OFDM) radar system exhibits inherent non-linearity which makes the accurate estimation of target's range and velocity hard to evaluate via conventional linear estimation technique like Fourier transform (FT). In this paper, a novel iterative non-linear kernel least mean square (KLMS) based estimation technique for target range estimation is proposed. Simulations demonstrate convergence of the proposed KLMS based estimator to a lower mean square error floor as compared to the existing FT based estimator.

Original languageEnglish
Title of host publicationIET Conference Publications
PublisherInstitution of Engineering and Technology
Number of pages5
EditionCP728
ISBN (Electronic)9781785614217, 9781785615030, 9781785616624, 9781785616723, 9781785616990, 9781785617072
ISBN (Print)9781785615078, 9781785615153
DOIs
Publication statusPublished - 28 May 2018
Externally publishedYes
Event2017 International Conference on Radar Systems, Radar 2017 - Belfast, United Kingdom of Great Britain and Northern Ireland
Duration: 23 Oct 201726 Oct 2017

Publication series

NameIET Conference Publications
NumberCP728
Volume2017

Conference

Conference2017 International Conference on Radar Systems, Radar 2017
Country/TerritoryUnited Kingdom of Great Britain and Northern Ireland
CityBelfast
Period23 Oct 201726 Oct 2017

Keywords

  • Delay estimation
  • Fourier transform
  • Kernel adaptive filtering
  • OFDM radar
  • RKHS techniques
  • Sparse signal processing

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