Four-Parameter Sinefit

Least squares sinusoid fit. Optimization toolbox not needed. Data can be non-uniformly sampled.

Description

Least squares sinusoid fit algorithm described in IEEE Standard for Digitizing Waveform Recorders (IEEE Std 1057): Algorithm for three-parameter and four-parameter least squares fit to sinewave data using matrix operations.

The algorithm is (in most cases) really quick. If the signal frequency is a guess, it has to be close to true frequency value.

For further information, consult IEEE Std 1057 and/or IEEE Std 1241 documentation.

Acknowledgements

The author wishes to acknowledge the following in the creation of this submission:
Modulo Time Plot

• MATLAB release: MATLAB 7.6 (R2008a)
• Other requirements: None. Should work on older MATLAB versions.

[Edwin]

The program worked fine for me it was exactly what I was looking for. I use it for the estimation of the SINAD and subsequent ENOB value. The method tends to shift more signal to the residual when the signal that is used gets longer.

[K E]

Here is an example with a regular sinusoid, which may be helpful:
t = 0:0.1:1000 ; % Time must be in seconds, not Matlab time
T = 10 ; % Period (s)
f = 1/T ; % Signal frequency (not sampling frequency!)
y = 2*sin(2*pi*t./T) ; % Sinusoid
[params, yest, yres, rmserr] = sinefit(y, t, f, 1, 1, 1) ;

[Daniel Wei]

This is actually a cosine fit, I think.