Annotation

Annotation: Objectives: System analysis of the functionality and reliability of the navigation system of an autonomous surface vessel. The main focus is on the study and modeling of the state of the vessel during its motion, including position, speed and heading angle, by analyzing the data provided by ambient light sensors, the transition from measurements to the representation of the state of the vessel in a two-dimensional navigation coordinate system is carried out. Part of the analysis is the study of how to convert the data from the inertial coordinate system to the navigational coordinate system, which is related to the consideration of angular parameters and nonlinear dynamics of the system. In addition, the study focuses on evaluating the effectiveness of data filtering algorithms, such as the unfiltered Kalman filter (UKF), and their ability to adequately reflect the ship's state under complex and changing external influences. The aim of the article is to conduct a systematic analysis of the processes of receiving and processing navigation system data, to identify possible error factors and to develop approaches to ensure the accuracy of estimation and stability of ship control in various operating conditions. Methods: The main results of the work were obtained using methods of mathematical analysis and modeling. Results: The navigation system of an autonomous vessel is considered with emphasis on the system analysis of its main components and algorithms. The model of motion in the navigation coordinate system based on acceleration and angular velocity data provided by inertial sensors is specified. The feasibility of transforming the measurements through the rotation matrix using the heading angle is shown, which allowed to reduce errors and improve the representation of motion parameters. The effectiveness of the unfiltered Kalman filter (UKF) in conditions of nonlinearity and external disturbances is analyzed, and its ability to provide stable and accurate estimation of the ship's state is confirmed. Conclusions: A proposed motion model using Kalman filter (UKF) to combine sensor data to improve navigational accuracy.