
А.E. Makarov1, I.M. Lerner2, I.V. Ryabov3
1,3 Volga Region State Technological University (Yoshkar-Ola, Russia)
2 Kazan National Research Technical University named after A.N. Tupolev–KAI (Kazan, Russia)
1 makarovaleksey2014@yandex.ru; 2aviap@mail.ru; 3ryabov22@mail.ru
Problem Statement. Positioning using global navigation satellite systems (GNSS) is a particularly complex task in urban environments, where a variety of natural and man-made objects can impair the propagation of signals from a direct line of sight to the user. Therefore, the problem of increasing the accuracy of positioning using algorithms for additional processing of information about the location of an object in navigation systems operating on the principle of receiving signals from global satellite navigation systems becomes relevant
Goal Development of an algorithm for increasing the accuracy of positioning of moving objects using signals from navigation satellite systems based on the processing of various types of signals in shadow conditions.
Results. A method for increasing the accuracy of positioning of moving objects is presented, based on the use of reliable and unreliable signals received by the navigation processor, by processing them using the point assessment method. The developed method allows increasing the accuracy of positioning in shadow conditions up to 1-1.5 meters. The implementation of the algorithm can be performed on any computing device capable of receiving navigation data and executing user commands.
Practical significance. An algorithm for increasing the accuracy of geo-positioning has been developed. The criteria for selecting navigation signals have been defined. For a more understandable interpretation of the positioning error, a method of transition to the metric coordinate system has been selected. An analysis of the algorithm's operation based on a theoretical sample of 16 values has been given. The theoretical accuracy of the operation has been determined.
The work was prepared as part of the implementation of work on priority 2030.
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