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11
Issue
vol 67 / November, 2024
Article

DOI 10.17586/0021-3454-2023-66-6-441-448

UDC 629.7.052.9

NEURAL NETWORK MODEL OF ERRORS OF AN AUTONOMOUS AIRCRAFT STRAPDOWN INERTIAL NAVIGATION SYSTEM

S. Alsayed
A. F. Mozhaisky Military Space Academy, Department of Autonomous Control Systems;


V. V. Efimov
A. F. Mozhaisky Military Space Academy, Department of Autonomous Control Systems;


I. V. Fominov
A. F. Mozhaysky Military Space Academy, Department of Autonomous Control Systems, St. Petersburg;


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Reference for citation: 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. Vol. 66, N 6. P. 441—448 (in Russian). DOI: 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.
Keywords: autonomous aircraft, strapdown inertial navigation system, error model, neural network, operating mode

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