Parameter estimation of multicomponent polynomial phase signals

This paper addresses the issue of detection and parameter estimation of multicomponent Polynomial Phase Signals (mc-PPS's) embedded in noise based on high-order ambiguity function (HAF). We first show how existing PHAF-based techniques (PHAF-product HAF) are inadequate mainly in providing reliable detection for mc-PPS. The main contribution of this paper is that we present a novel parameter estimation method. Firstly, given a set of time delay, it gives rise to a set of estimates of phase coefficients based on HAF. Then it produces a final estimate of phase coefficient by means of voting. The new method improves the probability of detection and estimation accuracy while avoiding the issue of threshold selection. Computer simulations are carried out to illustrate the advantage of the proposed method over existing techniques.