A new method to approximate the least squares multi-harmonic fitting is proposed. The basic idea is to expand in Taylor’s series the derivative on ω of the least squares cost function around a central value, so reducing the frequency estimation to a calculation of a root of a polynomial. In this way the method provides a frequency estimation in a closed form avoiding the recursion that is necessary in the classical approach. The results show that the proposed algorithm reaches the Cramer–Rao bound in a narrow range of frequency around a pre-estimation. Increasing the approximation orders of the Taylor’s expansion the range of maximum accuracy widens. This method is particularly suitable in grid frequency estimation due its low variability. The proposed algorithm, preserving the accuracy, requires an execution time up to 8 times lower compared to a single iteration of the classical recursive approach.
Giarnetti, S., Leccese, F., Caciotta, M. (2015). Non recursive multi-harmonic least squares fitting for grid frequency estimation. MEASUREMENT, 66(April 2015), 229-237 [10.1016/j.measurement.2015.02.021].
Non recursive multi-harmonic least squares fitting for grid frequency estimation
GIARNETTI, SABINO;LECCESE, Fabio;CACIOTTA, Maurizio
2015-01-01
Abstract
A new method to approximate the least squares multi-harmonic fitting is proposed. The basic idea is to expand in Taylor’s series the derivative on ω of the least squares cost function around a central value, so reducing the frequency estimation to a calculation of a root of a polynomial. In this way the method provides a frequency estimation in a closed form avoiding the recursion that is necessary in the classical approach. The results show that the proposed algorithm reaches the Cramer–Rao bound in a narrow range of frequency around a pre-estimation. Increasing the approximation orders of the Taylor’s expansion the range of maximum accuracy widens. This method is particularly suitable in grid frequency estimation due its low variability. The proposed algorithm, preserving the accuracy, requires an execution time up to 8 times lower compared to a single iteration of the classical recursive approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.