USE OF PARTICLE SWARM OPTIMIZATION ALGORITHM FOR DIGITALIZED SINEWAVE SIGNAL PARAMETERS ESTIMATION

Abstract

In the paper is proposed a procedure based on the particle swarm optimization algorithm for parameters estimation of sinewave signals as: amplitude, phase, frequency and offset. Differently from the classical method used to solve this problem (the sine-fitting algorithms), the proposed procedure considers the estimation problem as an optimization one. In fact, the particle swarm algorithm tends to global solution instead of a local solution. The proposed procedure preliminarily estimates the raw value of the parameters under investigation by a time analysis of the input signal. Successively, these values are used by the particle swarm algorithm for the final estimation result. The tests of the proposed procedure determine the most effective cost function for the algorithm and confirm that the achievable performances are in according with the sine fitting algorithm. Moreover, the execution time for the proposed procedure is lower than the sine fitting, making it an interesting alternative.