A Kalman filtering algorithm for the estimation of chirp signals in Gaussian noise [articol]

Abstract

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