Abstract:
The paper addresses the problem of
estimating the parameters of chirp signals 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 nonlinear but
exact measurement equation and guides the estimation
of the states of these signals to an extended Kalman
filtering algorithm. Procedure simulations were made on
linear and quadratic phase modulation signals with
time-varying amplitude and are consistent with the
theoretical approach. The results given by this new
algorithm are compared with the performances of a
standard Kalman technique.
