Cubic phase function for two-dimensional polynomial-phase signals

A cubic phase function for two-dimensional polynomial-phase signals of the third order (CPF 2-D) is proposed. The CPF 2-D based estimator is able to obtain all unknown parameters by using reduced number of phase differences, compared to the classical Francos-Friedlander (FF) approach. Statistical analysis shows that the proposed CPF 2-D based estimator is asymptotically unbiased and gives low mean squared error (MSE). Simulation results demonstrate that the proposed approach outperforms the FF approach.