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  • Research Article
  • Open Access

Clipped Input RLS Applied to Vehicle Tracking

  • Hadi Sadoghi Yazdi1Email author,
  • Mojtaba Lotfizad1,
  • Ehsanollah Kabir1 and
  • Mahmood Fathy2
EURASIP Journal on Advances in Signal Processing20052005:636894

https://doi.org/10.1155/ASP.2005.1221

Received: 24 July 2004

Published: 31 May 2005

Abstract

A new variation to the RLS algorithm is presented. In the clipped RLS algorithm (CRLS), proposed in updating the filter weights and computation of the inverse correlation matrix, the input signal is quantized into three levels. The convergence of the CRLS algorithm to the optimum Wiener weights is proved. The computational complexity and signal estimation error is lower than that of the RLS algorithm. The CRLS algorithm is used in the estimation of a noisy chirp signal and in vehicles tracking. Simulation results in chirp signal detection shows that this algorithm yields considerable error reduction and less computation time in comparison to the conventional RLS algorithm. In the presence of strong noise, also using the proposed algorithm in tracking of 59 vehicles shows an average of % reduction in prediction error variance relative to conventional RLS algorithm.

Keywords and phrases

RLSclipped input datanoise cancellationvehicle tracking

Authors’ Affiliations

(1)
Department of Electrical Engineering, Tarbiat Modarres University, Tehran, Iran
(2)
Faculty of Computer Engineering, Iran University of Science and Technology, Tehran, Iran

Copyright

© Yazdi et al. 2005

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