Adaptive frequency estimation using iterative DESA with RDFT-based filter

This paper proposes a new approach for estimating fundamental frequency of grid signals. The approach is based on a discrete-time energy separation algorithm (DESA) combined with an adaptive bandpass filter (BPF). The BPF is built using a discrete Fourier transform (DFT) and inverse DFT both used recursively. The technique is computationally efficient and robust to the harmonics and noise in the signal. The method's performance is validated by comparing the results with some existing algorithms.