Estimation of multicomponent polynomial phase signals of mixed orders (Q5958655)

This paper addresses the issue of detection and parameter estimation of multicomponent polynomial phase signals (mc-PPS) embedded in noise. We focus on analyzing a general class of mc-PPS in the sense that we allow the PPS to have (i) very different amplitudes, (ii) unknown phase orders, and (iii) unknown number of components. We first show how existing techniques are inadequate in providing reliable estimates for such a broad class of mc-PPS. High-order ambiguity function (HAF) and its product multi-lag variant (PHAF) are the basic tools that we use here. The main contribution of this paper is that we present a recursive algorithm that always starts with the lowest order HAF (or PHAF) to successively detect, estimate, and remove the PPS components. This is contrasted with prevailing mc-PPS estimation techniques, where the highest order HAF is first used and the PPS components are often assumed to have the same phase orders and like amplitudes. Computer simulations are carried out to illustrate the advantage of the proposed algorithm over existing techniques.