Adaptive Tracking of a Noisy Sinusoid/Chirp with Unknown Parameters

This paper presents an adaptive algorithm to track a sinusoid/chirped signal buried in additive noise. The chirped signal is a sinusoid whose frequency is drifting at a constant rate. After incorporating second order linear state space model of the sinusoid, SSRLS successfully tracks sinusoid/chirp with unknown parameters. The frequency estimation is done using a stochastic gradient like scheme. The forgetting factor for SSRLS and step size parameter for frequency estimator play important roles in this context

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