Parameter estimation of 2-D cubic phase signal using cubic phase function with genetic algorithm

Authors:
Igor Djurović;Pu Wang;Cornel Ioana
Affiliations:
University of Montenegro, Electrical Engineering Department, Cetinjski put bb, 81000 Podgorica, Montenegro;Stevens Institute of Technology, Department of Electrical and Computer Engineering, Hoboken, NJ 07030, USA and School of Electronic Engineering, University of Electronic Science and Technology of ...;INP Grenoble, Gipsa Lab, Grenoble, France
Venue:
Signal Processing
Year:
2010

Citing 13
Cited 1

Two-Dimensional Polynomial Phase Signals: Parameter Estimationand Bounds

Multidimensional Systems and Signal Processing
Signal-to-noise ratio estimation using higher-order moments

Signal Processing
A computationally efficient technique for estimating the parameters of polynomial-phase signals from noisy observations

IEEE Transactions on Signal Processing - Part II
Extending the Performance of the Cubic Phase Function Algorithm

IEEE Transactions on Signal Processing
Estimating parameters of multiple wideband polynomial-phase sourcesin sensor arrays

IEEE Transactions on Signal Processing
Parameter estimation of 2-D random amplitude polynomial-phasesignals

IEEE Transactions on Signal Processing
Optimal parameter selection in the phase differencing algorithm for2-D phase estimation

IEEE Transactions on Signal Processing
Product high-order ambiguity function for multicomponentpolynomial-phase signal modeling

IEEE Transactions on Signal Processing
Generalized High-Order Phase Function for Parameter Estimation of Polynomial Phase Signal

IEEE Transactions on Signal Processing - Part I
Model based phase unwrapping of 2-D signals

IEEE Transactions on Signal Processing
A fast algorithm for estimating the parameters of a quadratic FM signal

IEEE Transactions on Signal Processing
Asymptotic statistical analysis of the high-order ambiguity function for parameter estimation of polynomial-phase signals

IEEE Transactions on Information Theory
An estimation algorithm for 2-D polynomial phase signals

IEEE Transactions on Image Processing

Are genetic algorithms useful for the parameter estimation of FM signals?

Digital Signal Processing

Quantified Score

Hi-index	0.08

Visualization

Abstract

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 CPF to the 2-D PPS leads to a demanding three-dimensional (3-D) search an efficient implementation is proposed by using genetic algorithms. Simulation results demonstrate that the proposed approach outperforms the classical Francos-Friedlander technique in terms of lower SNR threshold.