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 …

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 …

The two‐dimensional (2D) cubic phase function (CPF) is known as a highly accurate 2D
polynomial phase signal estimator, but it has limited applicability due to the requirement for …

This paper considers refinement in parameter estimation of 2-D polynomial phase signals
(PPSs). For this purpose, a method based on phase unwrapping, filtering and polynomial …

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 …

Nonstationary signals are common in many environments such as radar, sonar,
bioengineering and power systems. The nonstationary nature of the signals found in these …

A novel approach for the parameter estimation of polynomial phase signals (PPSs) is
proposed. Unlike the existing methods, the proposed method uses the spectrum phase (SP) …

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 …

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 …

The 2-D quasi-maximum likelihood algorithm for estimation of 2-D polynomial phase signals
(2-D PPSs) is proposed. Estimation of all phase parameters is performed in an efficient …