ANALYSIS OF POLYNOMIAL-PHASE SIGNALS BY THE INTEGRATED GENERALIZED AMBIGUITY FUNCTION

The aim of this work is the performance analysis of a method for the d etection and parameter estimation of mono or multicomponent polynomial -phase signals (PPS) embedded in white Gaussian noise and based on a g eneralized ambiguity function. The proposed method is shown to be asym ptotically efficient for second-order PPS and nearly asymptotically ef ficient for third-order PPS's. The method presents some advantages wit h respect to similar techniques, like the polynomial-phase transform, for example, in terms of i) a closer approach to the Cramer-Rao lower bounds, ii) a lower SNR threshold, iii) a better capability of discrim inating multicomponent signals.