Methods for Monitoring and Diagnosing Space Communication and Orientation Subsystems

Monitoring of the state and behavior of spacecraft subsystems based on telemetry data is designed to continuously perform the tasks of controlling, controlling and maintaining the technical characteristics of a spacecraft. Increasing requirements for the characteristics of monitoring methods inevitably leads to a revision of the control technologies used and the need to create a scientific and technical reserve in the form of approaches, methods and technologies for building promising competitive space technology, including: technologies for building integrated information support for solving the problems of monitoring spacecraft subsystems; applied object-oriented systems of artificial intelligence, neural networks and high-performance computing for control, diagnostics and decision support. Currently, the following issues of monitoring the fault tolerance and reliability of space systems are relevant: the development of concepts for flight control centers that control multi-satellite systems and imply high reliability, processing of extra-large amounts of information, autonomy of operation, transfer offunctions on board, reduced human participation in control; analysis of possible failures; substantiation of the use of the on-board system for diagnostics, monitoring and localization of failures and malfunctions, restoration of working capacity; ensuring the maximum achievable (close to absolute) safety, eliminating the catastrophic consequences of possible failures of individual elements and subsystems; development and improvement of the methodology for setting requirements, assessing and controlling the quality and reliability of spacecraft and their components; improvement of international standardization of commercial rocket and space technology; optimal integrated risk management of space activities. The work is devoted to the control and diagnostics of subsystems of communication and orientation of the spacecraft. An artificial neural network, pair and multiple correlation functions are used as a mathematical apparatus to support the operator's decision making. It is shown that the methods make it possible to detect malfunctions and failures of sensors in real time. Calculations based on data obtained from spacecraft sensors are presented.