Abstract:
This paper proposes a simple yet effective signal
parameter measurement technique (SPMT) for the accurate
estimation of fundamental and harmonic parameters. The
proposed method is evolved from the design of adaptive
filter bank (AFB) on the basis of frequency spectrum of the
input signal and is preceded by compressive sensing (CS).
The AFB is capable to decompose the multifrequency
signal into its respective modes and CS has got an excellent
capability of providing an enhanced frequency resolution
in a relatively shorter window. The accuracy of the proposed method is verified on various numerical simulated
signal polluted by interharmonics, harmonics, noise, frequency offset, and real-time signal acquired from hardware
setup. A comparison with existing approaches viz. empirical wavelet transform, improved adaptive filtering, Prony,
exact model order-ESPRIT, sliding ESPRIT is also presented which demonstrates the superiority of the proposed
SPMT over other techniques
