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Abdoush, Y., Pojani, G. and Corazza, G.E. (2019) Adaptive Instantaneous Frequency Estimation of Multicomponent Signals Based on Linear Time-Frequency Transforms. IEEE Transactions on Signal Processing, 67, 3100-3112.
https://doi.org/10.1109/TSP.2019.2912132

has been cited by the following article:

• TITLE: Enhanced Wideband Frequency Estimation via FFT: Leveraging Polynomial Interpolation and Array Indexing

  AUTHORS: Kiran Jayarama, Chien-In Henry Chen

  KEYWORDS: Scalloping Loss, Goertzel’s Algorithm, Super-Resolution, Fast Fourier Transform (FFT), Decimation in Frequency (DIF), Decimation in Time (DIT), Spectral Leakage, Frequency Estimation

  JOURNAL NAME: Journal of Computer and Communications, Vol.12 No.1, January 15, 2024

  ABSTRACT: Accurate frequency estimation in a wideband digital receiver using the FFT algorithm encounters challenges, such as spectral leakage resulting from the FFT’s assumption of signal periodicity. High-resolution FFTs pose computational demands, and estimating non-integer multiples of frequency resolution proves exceptionally challenging. This paper introduces two novel methods for enhanced frequency precision: polynomial interpolation and array indexing, comparing their results with super-resolution and scalloping loss. Simulation results demonstrate the effectiveness of the proposed methods in contemporary radar systems, with array indexing providing the best frequency estimation despite utilizing maximum hardware resources. The paper demonstrates a trade-off between accurate frequency estimation and hardware resources when comparing polynomial interpolation and array indexing.