Clipped input RLS applied to vehicle tracking

Authors:
Hadi Sadoghi Yazdi;Mojtaba Lotfizad;Ehsanollah Kabir;Mahmood Fathy
Affiliations:
Department of Electrical Engineering, Tarbiat Modarres University, Tehran, Iran;Department of Electrical Engineering, Tarbiat Modarres University, Tehran, Iran;Department of Electrical Engineering, Tarbiat Modarres University, Tehran, Iran;Faculty of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2005

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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 3.06% reduction in prediction error variance relative to conventional RLS algorithm.