Identification of Energy-Hidden Chirp Signals of Telecommunication Systems in Conditions of Parametric Uncertainty

Abstract

The ambiguity diagram of rectangular chirp RF pulse has been analyzed. The characteristic point of ambiguity diagram was identified. It was proposed to identify the signal on the basis of correlation level at the characteristic point of ellipsoidal ambiguity diagram built in a special coordinate system. The quasi-optimal autocorrelation algorithm with quadrature processing is proposed. This algorithm is resistant to a priori uncertainty of parameters of input energy-hidden signals with unknown waveform and unknown initial phase against the background of Gaussian stationary noise. The tuning parameters of identification scheme and the decision-making rule regarding the availability of chirp signal in the input mixture were determined. The simulation modeling of identification procedure was conducted using the software package Matlab R2016a. The simulation results confirmed the ability of the proposed algorithm to identify the chirp signal in the input mixture at small values of the signal-to-noise ratio.