ANALYSIS OF THE CURRENT STATE OF THE ART OF SENSORS FOR INERTIAL NAVIGATION OF UNMANNED AERIAL VEHICLES

Abstract

Purpose. To investigate the current state of inertial sensors for navigation of unmanned aerial vehicles (UAVs), analyse their advantages, disadvantages, methods of error correction and integration with other navigation systems, as well as identify development prospects and current trends in this area.

Methodology. A systematic review of scientific literature, technical documents and studies related to various types of inertial sensors, their application in UAV navigation, and data fusion methods was conducted. A comparative analysis of modern technologies and methods to sensor integration is used.

Findings. The main types of inertial sensors, their advantages and disadvantages are identified, and the most effective methods of error correction and integration with other systems are revealed. Modern trends, such as the use of artificial intelligence, the development of microelectromechanical systems and the emergence of new types of sensors that contribute to the accuracy and reliability of UAV navigation, are investigated. Particular attention is paid to the integration of inertial measurement units (IMUs) with other navigation sensors, such as the Global Navigation Satellite System and visual sensors, to ensure more reliable and accurate navigation. Error correction methods, such as the Kalman filter and adaptive filters, used to improve the accuracy of navigation systems are systematised.

Originality. For the first time, the types of inertial sensors are systematized and analyzed, and data on their advantages and disadvantages in the context of navigation requirements in modern UAV navigation systems are determined.

Practical value. The results obtained can be used to improve UAV navigation systems, increase their reliability and accuracy. Recommendations for the selection and integration of sensors will contribute to the development of new technologies in the field of unmanned aerial vehicles.