Development of self-organizing algorithms for the navigation system of an unmanned aerial vehicle

Authors: Tan Wei, Bai Fan
Published in issue: #10(39)/2019
DOI: 10.18698/2541-8009-2019-10-532
Category: Informatics, Computer Engineering and Control | Chapter: System Analysis, Control, and Information Processing, Statistics
Keywords: navigation, self-organization, short-term forecast, long-term forecast, Kalman filter, error compensation, mathematical model, linear trends
Published: 04.10.2019

Inertial navigation systems (INS) with satellite corrections are the most accurate. However, sometimes it is not possible to use the correction signal from satellites, therefore, it is necessary to build a predictive model to compensate the error. The self-organization method allows one to build a predictive model of INS errors. The article analyzes the short-term and long-term forecast, typical models are proposed. The use of the model building algorithm for forecasting allows one to check the operability of the algorithm for generating the mathematical model of INS errors based on the self-organization method. Algorithmic correction of an autonomous INS (when an autonomous INS operation was preceded by a corrected mode) using an algorithm for constructing a predictive model, as well as self-organization and forecast algorithms using an INS error model, can improve the accuracy of UAV navigation definitions.

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