Bayesian estimation of the parameters of a polynomial phase signal using MCMC methods

The aim of this paper is Bayesian estimation of the parameters of a polynomial phase signal. This problem, encountered in radar systems for example, is usually solved using a time-frequency analysis or phase-only algorithms. A Bayesian approach using Markov chain Monte Carlo (MCMC) methods for estimating a posteriori densities of the polynomial parameters is proposed. The main advantage of this approach is that it gives a direct estimation of all polynomial coefficients, contrary to previously developed algorithms.