The estimation of chirp signals parameters by an extended Kalman filtering algorithm

This paper addresses the problem of estimating linear and quadratic chirp signal parameters. We consider an estimation method based on an approximate linear state space representation of the chirp signal. This approach offers the opportunity to use an extended Kalman filtering procedure in view to estimate the parameters of polynomial phase signals. Procedure simulations were made on linear and quadratic chirp sinusoids with time-varying amplitude embedded in additive white Gaussian noise and are consistent with the theoretical approach. The paper presents the most important results.