Multilag high-order ambiguity function for multicomponent polynomial phase signal modeling

The aim of this paper is the proposal and the performance analysis of a method for estimating the parameters of multicomponent polynomial-phase signals (PPS) embedded in white Gaussian noise. The paper initially describes the identiflability problem arising with existing approaches when dealing with multicomponent PPS having the same highest order phase coefficients. This situation arises in a number of practical applications, such as synthetic aperture radars or propagation of polynomial-phase signals through channels affected by multipath and is thus worthy of a careful analysis. A new approach is proposed based on a transformation called the multiplicative multi-lag high order ambiguity function (mml-HAF). The use of the mml-HAF offers a number of advantages with respect to the HAF, in terms of removal of the identiflability problem and better noise rejection capabilities. The theoretical performance of the method is evaluated and verified by simulation results.