Adaptive Detection of Normal Mixture Signals with Pre-Estimated Gaussian Mixture Noise

Abstract

The paper describes the adaptive method of estimating the parameters of the distribution of the useful signal under the assumption that the noise distribution can be pre-estimated. It is based on the method of moving separation of the finite normal mixtures and implemented for the estimating both signal-noise and signal distribution parameters. We assume that the probability distribution of the signal, signal with noise and “pure” noise can be presented in form of finite normal mixtures. Also, a method for change point detection based on testing the homogeneity hypothesis using the Kolmogorov criterion is proposed.