THE OPTIMAL STATE ESTIMATION FUSION ALGORITHM IN DISCRETE-CONTINUOUS AUV SYSTEMS
Abstract
The article is focused on the optimal state estimation fusion algorithm for discrete-continuous systems.
The aim of the study is to create an effective fusion strategy for combining data obtained from continuous
and discrete information sources to improve the accuracy and reliability of state estimation in
complex dynamic systems. The paper discusses in detail the theoretical foundations of the proposed method,
including the mathematical description of the continuous and discrete system models, the optimization
criterion formulation, and the derivation of equations for calculating the complementation weights. Particular
attention is paid to the analysis of conditions under which the proposed algorithm provides an
improvement in estimation accuracy compared to the use of only continuous or only discrete filter.
The authors present the results of numerical modeling demonstrating the developed algorithm efficiency
on the example of autonomous underwater vehicle motion parameter estimation. It is shown that the proposed
fusion method allows to significantly reduce the estimation errors compared to the use of separate
filters, especially in conditions of incompleteness and noise in measurements. In conclusion, it is stated
that the developed algorithm is promising for application in various fields related to information processing
in complex technical systems, such as navigation, motion control, monitoring of the objects and
processes. It is noted that the proposed approach can be generalized to the case of complexing data from
a larger number of information sources and adapted to different types of discrete-continuous systems.
The article is considered to be valuable for specialists in control theory, signal and information processing,
as well as for developers of navigation and motion control systems. The research results can find practical
application in the creation of high-precision state estimation systems in various technical applications.
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