Adaptive Integrated Navigation Algorithms for Advanced Avionics Systems of High-Dynamic Aircrafts

Information estimation, prediction and fusion algorithms are of great importance for high-dynamic aircraft. In this paper, we introduce a selective navigation system, which can work in a "update mode" using Kalman filter and in a "prediction mode" via self-organization algorithms...

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Bibliographic Details
Main Authors: Zhu, Yixiao, Liu, Tingxin, Zuo, Siqi, Neusypin, K.A., Proletarsky, Andrey
Format: Conference Proceeding
Language:English
Subjects:
accuracy evaluation methodology
Aircraft navigation
avionics system
Heuristic algorithms
high-dynamic aircraft
Information processing
Integrated navigation
Kalman filtering
Kalman filters
Prediction algorithms
Software algorithms
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Summary:Information estimation, prediction and fusion algorithms are of great importance for high-dynamic aircraft. In this paper, we introduce a selective navigation system, which can work in a "update mode" using Kalman filter and in a "prediction mode" via self-organization algorithms. We derived a formula of positioning error, functioning as an accuracy evaluation criterion, in order to evaluate the accuracy of different integrated navigation algorithms online. Thus, we can select the most suitable algorithm for current time moment, and switch the system structure from one mode to another, according to the dynamic model of inertial navigation system. To testify the correctness of the proposed evaluation methodology, real laboratory tests are carried out under a half-real environment. According to the results, the evaluation methodology can provide comparison results of different integrated algorithms. In addition, self-organization algorithms and genetic algorithms with high reliability of information processing can greatly improve the performance and adaptability of integrated navigation systems.
ISSN:2161-2927
DOI:10.23919/CCC52363.2021.9549402