A.V. Ivanov - Dr.Sc. (Eng.), Associate Professor, Professor, Head of «Radiotekhnika» Department, 

Tambov State Technical University

E-mail: Aleksandr-Ivanov68@yandex.ru

V.O. Surkov – Aspirant, 

Tambov State Technical University

E-mail: surkov-v@mail.ru

The article discusses the issues of the creation of optimal identification algorithms and adaptive estimation of discrete-continuous processes. 

When using satellite radio navigation systems in navigation systems, it is necessary to solve several problems at the same time: estimation coordinates and motion parameters of mobile objects; evaluation of radio signals at the input of satellite radio navigation signals receiving equipment; evaluation of the transmitted service information; control of the integrity of navigation data.

Theoretically, the solution of these problems can be reduced to solving the identification problem and adaptive discrete-continuous processes estimation. A special feature of the problem is that with the discrete-continuous processes their estimation is carried out jointly with identifying a slowly varying continuous process task, which is considered as a parametric estimation problem. Novelty consists in the fact that a discrete process is a two-component composite process, each component of which is a vector process, and a continuous process is a multi component diffusion process.

The problem of synthesis for optimal identification algorithms and discrete-continuous processes adaptive estimation is formulated. A mathematical model in the discrete Markov processes form is used to describe the change of discrete processes states. A continuous process is a multi component diffusion process, the change of which in time is described by a vector-matrix differential stochastic equation.

To obtain optimal algorithms, a joint vector discrete-continuous process is formed. The optimal algorithms for identification and adaptive estimation of discrete-continuous processes are obtained by the Markov theory methods of estimating random processes by the maximum a posteriori probability density criterion. According to the obtained algorithms, multi channel information processing is performed. In each channel, estimates of the samples of the conditional continuous and two-component discrete conditional vector processes are determined. The channels number depends on the slowly varying continuous process possible values number, the identification of which is carried out. As the true values of the estimates of the samples of the conditional continuous and twocomponent discrete conditional vector processes, those values are obtained, that are in the channel, for which the posterior probability of the value of the identifiable slowly varying continuous process is maximal.

Using statistical computer modeling methods, we investigated the effect of the number of information processing channels on the a posteriori recognition probability and on the time of identification of the reliability parameter of navigation data of satellite radio navigation systems.

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