A comparative performance analysis of some fast and accurate frequency estimators

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Thesis Type: Postgraduate

Institution Of The Thesis: Bursa Uludağ University, FEN BİLİMLERİ ENSTİTÜSÜ, Turkey

Approval Date: 2020

Thesis Language: Turkish

Student: Sevim Hazal Uz

Supervisor: ERDOĞAN DİLAVEROĞLU

Abstract:

Instantaneous estimation of the frequency of a real sinusoid in noise from a small number of data samples is an important problem in the signal processing area. Several frequency estimators are proposed for this problem in the literature. In this thesis, some of the popular ones including the discrete energy separation algorithms (DESAs) are considered. Using a Taylor series expansion technique, very simple and yet accurate closed form expressions for the bias and the variance of the estimators are derived. Computer simulations are included to validate the theoretical results.