METHOD OF MOVING OBJECT POSITIONING WITHOUT USING GLOBAL GEO-REFERENCED DATA
Cite as: E.V. Lishchenko, E.V. Melnik, A. S. Matvienko, A.Yu. Budko. Method of moving object positioning without using global geo-referenced data // Izvestiya SFedU. Engineering Sciences – 2024. – N. 6. - P. 85-96. doi: 10.18522/2311-3103-2024-6-85-96
Abstract
The paper considers the problem of determining the current coordinates of moving object in the
conditions of unstable signal from the global navigation satellite system (GNSS). The relevance of the
work is due to the fact that in recent years moving object are increasingly used in virtually all sectors of
industry, agriculture, transportation, solving a variety of tasks of surveillance, reconnaissance, monitoring
the state of controlled objects, search and rescue operations, cargo delivery and much more. At the same
time, the success of flight missions largely depends on how accurately and efficiently its onboard navigation
system works in real time. The existing solutions for creating onboard positioning systems involve the
use of inertial and GNSS. However, they have the disadvantage of partial or complete absence of data
from the GNSS (Global Positioning System). This paper describes a method for maintaining a given accuracy
of moving object spatial positioning under conditions of partial or complete absence of data from the
object's GSP. This approach is based on a combination of computer vision methods for processing video
stream frames from the moving object on-board vision system (OVS) in order to ensure positioning accuracy
under conditions of partial or complete absence of data from satellite navigation systems. Based on
the advanced method, an algorithm has been developed for automated determination of moving object
coordinates in the absence of georeferencing data from global positioning systems (GPS). Experiments
have been carried out, which demonstrated the reduction of time costs for description and matching of key
points and improvement of the accuracy of image matching. The developed algorithm was used to solve
the problem of satellite image matching, which is an important step in the moving object positioning problem
without the use of global geo-referencing data.
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