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scientific edition of Bauman MSTU

SCIENCE & EDUCATION

Bauman Moscow State Technical University.   El № FS 77 - 48211.   ISSN 1994-0408

An Integrated Unmanned Aerial Vehicle Navigation System Capable of Fault Detection and Isolation

# 12, December 2016
DOI: 10.7463/1216.0852517
Article file: SE-BMSTU...o206.pdf (2671.45Kb)
authors: KeKe Gen1,*, N.A. Chulin1



1 Bauman Moscow State Technical University, Moscow, Russia

The article discusses an integrated navigation system development for unmanned aerial vehicles (UAVs) to provide fault detection and isolation. In case an UAV operates flights in independent mode or in remote pilot control under conditions when an operator has a lack of information on the environment, the single-source information cannot ensure appropriate precision to navigate the UAV. Therefore, the UAV, certainly, needs an integrated navigation system based on the merger of navigation information from the several sources to enable compensation for the shortcomings of each of the sources.
The integrated navigation system typically combines two or more than two types of navigation systems. Thus, an integrated navigation system can take full advantage of the complementarity of various navigation systems and generate accurate navigation information. Such systems typically include an inertial measurement unit (Inertial Measurement Units - IMU), SNA, visual navigation system, etc. However, in practical applications, there are many factors that affect the accuracy and reliability of the measured data, such as data transmission errors, ambient noise, and systematic errors of sensors, etc. Therefore, the fault detection and isolation feature is also necessary for the integrated navigation system.
The article offers an integrated navigation system for UAV based on conversion of navigation modes, Kalman filter, and merge of navigation information from the several sources, namely a SNA system, visual navigation system based on the algorithm of simultaneous localization and mapping (Simultaneous Localization And Mapping - SLAM), barometric altimeter, altimeter and inertial navigation system (INS). Such an integrated navigation system is capable not only to provide detection and isolation of low reliable navigation information on the basis of the residual errors of the test "chi-squared" and the result of the test "chi-squared" with two state predictions, but also to use the advantages of various sensors to improve reliability of navigation data. The results of simulation in Matlab and system layout in a natural environment show that the proposed system has high accuracy of navigation and the capability to provide fault detection and isolation.

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