This overview paper presents and compares different methods traditionally used for estimating damped sinusoid parameters. Firstly, direct nonlinear least squares fitting the signal model in the time and frequency domains are described. Next, possible applications of the Hilbert transform for signal demodulation are presented. Then, a wide range of autoregressive modelling methods, valid for damped sinusoids, are discussed, in which frequency and damping are estimated from calculated signal linear self-prediction coefficients. These methods aim at solving, directly or using least squares, a matrix linear equation in which signal or its autocorrelation function samples are used. The Prony, Steiglitz-McBride, Kumaresan-Tufts, Total Least Squares, Matrix Pencil, Yule-Walker and Pisarenko methods are taken into account. Finally, the interpolated discrete Fourier transform is presented with examples of Bertocco, Yoshida, and Agrež algorithms. The Matlab codes of all the discussed methods are given. The second part of the paper presents simulation results, compared with the Cramér-Rao lower bound and commented. All tested methods are compared with respect to their accuracy (systematic errors), noise robustness, required signal length, and computational complexity.

JO - Metrology and Measurement Systems L1 - http://sd.czasopisma.pan.pl/Content/89815/PDF/Journal10178-VolumeXVIII+Issue4_01paper.pdf L2 - http://sd.czasopisma.pan.pl/Content/89815 IS - No 4 EP - 528 KW - damped sinusoids KW - frequency estimation KW - damping estimation KW - linear prediction KW - subspace methods KW - interpolated DFT ER - A1 - ZieliĆski, Tomasz A1 - Duda, Krzysztof PB - Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation JF - Metrology and Measurement Systems SP - 505 T1 - Frequency and Damping Estimation Methods - An Overview UR - http://sd.czasopisma.pan.pl/dlibra/docmetadata?id=89815 DOI - 10.2478/v10178-011-0051-y