A Signal Parameter Measurement Technique for Adversely Distorted Multifrequency Grid Signals

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.