Method for joint calibration of inertial sensors of an unmanned aerial vehicle using neural networks

The article deals with methods and technical means of control and testing samples of information-measuring and control systems intended for installation on unmanned aerial vehicles. The principles of creation of control systems built on inertial sensors of various types are considered. Shortcomings are revealed in the use of traditional methods of development based on direct readings from sensors with the help of software. The design of modern inertial sensors with indication of their components and parts is described. The technology of creating a test bench for evaluating the accuracy of sensor calibration is defined. Formulas on which the work of the test bench is based on its geometry are given. Specifies formulas used in the traditional method of calculating values from inertial sensors. Describes the process of learning the neural network to compensate for the disadvantages inherent in a traditional calibration method. The experiment of comparing actual values with the values obtained during the calculations is demonstrated. The traditional method of joint inertial sensor calibration is compared with the method based on neural networks. The advantages of using this method of inertial sensor calibration under the requirements of modern control systems are determined.

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