Abstract

In the processing of dynamically changing data, for example, radar data (RD), a crucial part is made by the representation of various data sets containing information about routes and signs of air objects. In the practical implementation of the computational process, it previously seemed natural that RD processing in data arrays was carried out by the elementwise search method. However, the representation of data arrays in the form of matrices and the use of matrix math allow optimal calculations to be formed during tertiary processing. Forming matrices and working with them requires a significant computational resource, so the authors can assume that a certain gain in calculation time may be achieved if there is a large amount of data in the arrays, at least several thousand messages. The article shows the sequences of the most frequently repeated operations of tertiary network processing, such as searching for and replacing an array element. The simulation results show that the processing efficiency (relative reduction of processing time and saving of computing resources) with the use of matrices, in comparison with elementwise search and replacement, increases in proportion to the number of messages received by the information processing device. The most significant gain is observed when processing several thousand messages (array elements). Thus, the use of matrices and the mathematical apparatus of matrix math for processing arrays of dynamically changing data can reduce processing time and save computational resources. The proposed matrix method of organizing calculations can also find its place in the modeling of complex information systems.

Highlights

  • In the processing of dynamically changing data, for example, radar data (RD), a crucial part is made by the representation of various data sets containing information about routes and signs of air objects

  • In the practical implementation of the computational process, it previously seemed natural that RD processing in data arrays was carried out by the elementwise search method

  • The representation of data arrays in the form of matrices and the use of matrix math allow optimal calculations to be formed during tertiary processing

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Summary

Technologies and production

In the processing of dynamically changing data, for example, radar data (RD), a crucial part is made by the representation of various data sets containing information about routes and signs of air objects. The representation of data arrays in the form of matrices and the use of matrix math allow optimal calculations to be formed during tertiary processing. The use of matrices and the mathematical apparatus of matrix math for processing arrays of dynamically changing data can reduce processing time and save computational resources. В обработке динамически изменяющихся данных, в частности, при третичной обработке радиолокационной информации [1, 2] важную роль играет вид представления различных массивов данных, содержащих динамическую информацию о трассах и признаках воздушных объектов. Представление массивов данных в виде матриц и применение методов матричной алгебры при операциях с ними вместо поэлементного поиска позволяют оптимальным образом сформировать вычисления при третичной обработке. Что на сервере, как устройстве обработки радиолокационной информации, имеется информация о среднеквадратичных отклонениях (СКО) по координатам и составляющим скоростей воздушных объектов от источников, выдающих РЛИ

Алгоритм третичной сетевой обработки и операции с матрицами
Elementwise search in the source array data
Boolean matrix
Формирование матрицыстолбца с новыми данными
Обработка повторных сообщений от источников радиолокационной информации
Replacing a column in the server SBM
Список ИСПОЛЬЗОВАННЫХ ИСТОЧНИКОВ
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