The estimation of polynomial-phase signals (PPSs) is a multiparameter problem, and the
maximum likelihood (ML) optimization functions have numerous local optima, making the …

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 …

In this paper, we consider parameter estimation of high-order polynomial-phase signals
(PPSs). We propose an approach that combines the cubic phase function (CPF) and the …

This paper presents a generalization of cubic phase function (CPF) for two-dimensional (2-
D) cubic phase polynomial phase signals (PPS). Since a straightforward application of the …

This article provides an overview of the cubic phase function (CPF) as a tool proposed for
both parametric and nonparametric estimation of the frequency modulated (FM) and in …

This paper considers parameter estimation of a new coupled mixture of polynomial phase
signal (PPS) and sinusoidal frequency modulated (FM) signal, recently introduced for …

The high-order phase function (HPF) has been introduced recently to estimate the
parameters of a polynomial phase signal (PPS). In this correspondence, we generalize the …

Parameter estimation of polynomial phase signals (PPSs) based on the cubic phase
function (CPF) and its extensions cannot be performed by using the fast Fourier transform …

Several papers have been published recently on the quasi-maximum likelihood (QML)
approach for the polynomial phase signals (PPS) parameter estimation. The QML is …

A novel approach for the parameter estimation of the polynomial phase signals (PPS) based
on the short‐time Fourier transform (STFT) is proposed. Estimator accuracy is significantly …