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Algorithms and Configuration for a Moving Object Attitude Control System Based on Microelectromechanical Sensors

Authors: Ibrahim M.A., Luk'yanov V.V. Published: 05.06.2020
Published in issue: #2(131)/2020  
DOI: 10.18698/0236-3933-2020-2-44-58

 
Category: Informatics, Computer Engineering and Control | Chapter: System Analysis, Control, and Information Processing  
Keywords: navigation, attitude, strap-down inertial navigation systems, microelectromechanical sensors, magnetometer, global navigation satellite systems, Kalman filter

Inertial systems for attitude control, stabilisation and navigation of moving objects boast a range of unique qualities, the most important of which are autonomy and interference immunity. At present, strap-down inertial navigation systems using inexpensive and compact microelectromechanical sensors are popular. The biggest disadvantage of the attitude control systems utilising microelectromechanical sensors is rapid error accumulation over time. The main error sources in strap-down inertial navigation systems are the errors of angular velocity sensors and accelerometers. Currently the accuracy required is ensured by the attitude control system processing the following two signals simultaneously: the magnetometer signal and the signal received from global navigation satellite systems such as GPS (NAVSTAR) and/or GLONASS. We developed an unconventional approach to integrating the two systems, that is, a strap-down inertial navigation system and a global navigation satellite system. It involves using the difference between the accelerations computed according to the global navigation satellite systems and those computed by the acelerometers and transformed to the geographic coordinate system for evaluating and compensating for the error of attitude angle assessment via the kinematic channel. Since this approach does not use integration of accelerometer readings, the attitude angle errors at the initial stage do not accumulate over time. Numerical simulation results of the algorithms developed show that the attainable attitude angle estimation accuracy significantly exceeds the accuracy of conventional methods

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