Title :
A method for parameters estimation of multiple sinusoids signal based on ANFs and SGA
Author :
Li, Ming ; Tu, Yaqing ; Su, Dan
Author_Institution :
Dept. of Inf. Eng., Logistical Eng. Univ., Chongqing, China
Abstract :
An iterative algorithm based on Adaptive notch filters (ANFs) and Sliding Goertzel algorithm (SGA) for the parameters, i.e. amplitudes, phases and frequencies, estimation of multiple sinusoids signal buried in noise especially in colored noise is proposed in this paper. Firstly, it uses ANFs to accurately estimate frequencies of sinusoids signal at every sample point. Secondly, the SGA computes Fourier coefficients for each sinusoid at the estimated frequencies. Thirdly, the parameters of multiple sinusoids are obtained. This approach is really different from other discrete spectrum correction methods that use DFT off-line to get the parameters estimation values for multiple sinusoids and the proposed visual method is on-line and provides a effectively, accurately and significant computational advantage. Extensive simulation tests have also been performed to verify the effectiveness of the ANFs and SGA based algorithm.
Keywords :
adaptive filters; amplitude estimation; discrete Fourier transforms; frequency estimation; iterative methods; notch filters; phase estimation; signal denoising; ANF; DFT; Fourier coefficients; SGA; adaptive notch filters; colored noise; discrete spectrum correction methods; frequency estimation; iterative algorithm; multiple sinusoid signal parameter estimation method; sliding Goertzel algorithm; visual method; Adaptive filters; Colored noise; Filtering algorithms; Frequency estimation; Resonant frequency; Time frequency analysis; Adaptive notch filters (ANFs); Sliding Goertzel algorithm (SGA); multiple sinusoids signal; parameters estimation;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
DOI :
10.1109/WCICA.2012.6359198