Variance and Threshold Level of the Least Squares Pitch Estimator with Windowed Data
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
Asilomar Conference on Signals, Systems, and Computers (ACSSC 2023)
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Estimating the pitch of a periodic signal, also referred to as fundamental frequency, plays an import role in many signal processing applications. The well-known DTFT-based approximate nonlinear least squares (LS) pitch estimator is of great practical importance since it allows for a low-complex fast Fourier transform (FFT)-based implementation. In case of additive white Gaussian noise (AWGN), this estimator is the maximum liklihood estimator (MLE) and asymptotically attains the Cram´er-Rao lower bound (CRLB). Windowing the data for side lobe suppression is necessary for many practical applications. This is especially important if we have interference signals
or harmonics of different order of magnitude. In this paper we provide an expression for the asymptotic variance of the estimator for windowed data. Furthermore, the influence of windowing on the threshold effect is investigated.
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