Neural network model of errors of an autonomous aircraft strapdown inertial navigation system
https://doi.org/10.17586/0021-3454-2023-66-6-441-448
Abstract
A neural network model is proposed for a strapdown inertial navigation system (SINS) entering an integrated inertial-satellite navigation system of an autonomous aircraft, operating in the conditions of loss of satellite radio navigation field signals. The model takes into account the main factors that define the errors in navigation parameters estimates by means of the SINS, including the dynamics of the aircraft functioning process. As essential parameters characterizing the autonomous aircraft flight mode dynamics, it is proposed to use linear and angular accelerations, as well as their variations in the discrete interval of the navigation system operation. A functional diagram of the inertial-satellite navigation system with the neural network model of SINS errors is presented, and recommendations are given for its specific implementation.
About the Authors
S. Alsayed
A.F. Mozhaisky Military Space Academy
Russian Federation
Russian Federation
Saeed Alsayed — Adjunct; A.F. Mozhaisky Military Space Academy, Department of Autonomous Control Systems.
St. Petersburg
V. V. Efimov
A.F. Mozhaisky Military Space Academy
Russian Federation
Russian Federation
Vladimir V. Efimov — Dr. Sci., Professor; A. F. Mozhaisky Military Space Academy, Department of Autonomous Control Systems.
St. Petersburg
I. V. Fominov
A.F. Mozhaisky Military Space Academy
Russian Federation
Russian Federation
Ivan V. Fominov — Dr. Sci., Professor; A.F. Mozhaisky Military Space Academy, Department of Autonomous Control Systems; Head of the Department.
St. Petersburg
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Review
For citations:
Alsayed S., Efimov V.V., Fominov I.V. Neural network model of errors of an autonomous aircraft strapdown inertial navigation system. Journal of Instrument Engineering. 2023;66(6):441-448. (In Russ.) https://doi.org/10.17586/0021-3454-2023-66-6-441-448
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