M.N. Chesnokov – Dr.Sc. (Eng.), Professor, Deputy Head of Department,

LTD «STC» (St. Petersburg)

E-mail: chesnokovmn@yandex.ru

Markov signal and interference models have become very useful in radio systems for designing of signal processing algorithms with respect to background interference. This leads to a significant radio systems efficiency increase. 

In this article, a novel algorithm for nonlinear filtering of a vector Markov process with continuous phase space in discrete time and vector observation under non-Gaussian noise with uncorrelated samples is obtained. This algorithm is described by an equation system for estimating of Markov process components and posterior distribution cumulants. Proposed algorithm is synthesized in discrete time and is intended for direct digital implementation.

Nonlinear state and observation equations are used in algorithm synthesis, and noise is assumed to be non-Gaussian with a known one-dimensional probability density function. This, as well as the ability to use multiple receiving paths allows to more precisely take into account real conditions.

It is shown that, depending on the method of choosing initial estimates, various modifications of the algorithm are possible.

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