Identification of time-Varying frequency of noiseless sinusoidal signal

TL;DR

This paper introduces a novel algorithm for estimating the time-varying frequency of noiseless sinusoidal signals, leveraging linear regression and gradient tuning to handle unknown, time-dependent amplitude and frequency functions.

Contribution

It presents a new gradient tuning algorithm that estimates time-varying frequency and amplitude of sinusoidal signals modeled by differential equations.

Findings

Algorithm effectively estimates frequency in noiseless signals.

Computer simulations demonstrate high accuracy and efficiency.

Procedure for synthesizing the algorithm is detailed.

Abstract

A new algorithm for estimating the time-varying frequency of a noiseless sinusoidal signal is considered. It is assumed that the amplitude and frequency of the sinusoidal signal are unknown functions of time, but are solutions of linear stationary differential equations with known parameters. The problem is solved using gradient tuning algorithms based on a linear regression equation obtained by parameterizing the original nonlinear sinusoidal signal. The example presented in the article and the results of computer modeling illustrate the efficiency of the proposed algorithm, as well as explain the procedure for its synthesis.