An improved Multi-harmonic Sine Fitting Algorithm based on Tabu Search

摘要

In the Multi-harmonic Fitting Algorithm based on four parameters sine fitting, the problem is that the global convergence highly depends on the initial estimation frequency. To overcome this problem, an improved Multi-harmonic Sine Fitting Algorithm based on Tabu Search (TSMSFA) is introduced. Combining Tabu Search theory, TSMSFA algorithm can converge to the global minimum with the initial frequencies obtained by Interpolation Discrete Fourier Transform (IpDFT) while multiharmonic signals are disturbed by additive noise, phase noise and jitter. The iteration process of TSMSFA is improved by adjusting the first iteration step-size. Compared with the execution speed of the Classical Multi-harmonic Sine Fitting Algorithm (CMSFA), TSMSFA has some improvement. (C) 2014 Elsevier Ltd. All rights reserved.