Joint Signal Parameter Estimation in Non–Gaussian Noise by the Method of Polynomial Maximization

This paper considers the adaptation of the method of polynomial maximization for synthesis of the polynomial algorithms of joint signal parameter estimation in non-Gaussian noise. It is shown that the nonlinear processing of samples, the moment and the cumulant description of random variables in the form of cumulant coefficients of the third and higher orders can decrease the variance of joint parameters estimation as compared with the well-known results.