A new class of multilinear functions for polynomial phase signal analysis
IEEE Transactions on Signal Processing
Efficient estimation of a narrow-band polynomial phase signal impinging on a sensor array
IEEE Transactions on Signal Processing
A low complexity blind estimator of narrowband polynomial phase signals
IEEE Transactions on Signal Processing
Performance of instantaneous frequency rate estimation using high-order phase function
IEEE Transactions on Signal Processing
Are genetic algorithms useful for the parameter estimation of FM signals?
Digital Signal Processing
| Hi-index | 0.01 |
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 standard HPF by introducing multiple time instants. Thus, the standard HPF can be treated as a special example of the generalized HPF with identical time instants. We propose a procedure for finding time instants minimizing the mean-square error (MSE). The proposed method achieves better performances than the high-order ambiguity function (HAF) and polynomial Wigner-Ville distribution (PWVD). The theoretical analysis as well as the Monte Carlo simulations verify the advantages such as lower MSE and lower SNR threshold for the PPS.