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Clipped Input RLS Applied to Vehicle Tracking

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.

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Correspondence to Hadi Sadoghi Yazdi.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Yazdi, H.S., Lotfizad, M., Kabir, E. et al. Clipped Input RLS Applied to Vehicle Tracking. EURASIP J. Adv. Signal Process. 2005, 636894 (2005). https://doi.org/10.1155/ASP.2005.1221

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Keywords and phrases

  • RLS
  • clipped input data
  • noise cancellation
  • vehicle tracking