Determination of the effective dimension of big data arrays containing satellite coordinates

Every day, satellites send coordinates to correct the parameters of its orbit from the ground control station. The coordinates are an array of large data. For storing and working with data, it is advisable to reduce the dimension of the big data array. This problem can be solved by using dimension r...

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Bibliographic Details
Main Authors: Sadikov, M. A., Mironenko, V. V., Savelyeva, A. A., Polyakova, A. S.
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Arrays
Big Data
Differential equations
Global navigation satellite system
Ground stations
Mathematical analysis
Satellites
Online Access:Get full text
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Summary:Every day, satellites send coordinates to correct the parameters of its orbit from the ground control station. The coordinates are an array of large data. For storing and working with data, it is advisable to reduce the dimension of the big data array. This problem can be solved by using dimension reduction methods. There are many methods, two methods will be considered in this paper: the NIPALS algorithm and box-counting. This is one of the ways one of the main ways to reduce the dimension of data by losing the least amount of information. By applying them, in addition to reducing the dimension of data arrays, it is additionally possible to avoid the need to solve a system of differential equations, which will speed up the calculation of satellite coordinates. As is known, the accuracy of determining the coordinates of ground points using GNSS technologies depends on the accuracy of the satellite’s position.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0094299