Recent advances in the estimation of the polynomial-phase signals

This paper reviews recent advances in the parameter estimation of higher-order polynomial-phase signals (PPSs). The maximum likelihood (ML) technique is the most accurate estimation procedure, but requirements for multidimensional search limits its practical application to third-order PPSs. To enable estimation of higher-order PPSs in real time, techniques, based on the phase differentiation (PD), are proposed. Each PD reduces the search dimensions, but, at the same time, degrades the estimation performance. In this paper, we consider two approaches for performance improvement of PPS estimation techniques. The first one is based on the search optimization by using genetic algorithms, while the second one consider lower number of PDs and one dimensional search.