Method for quickly extracting on-orbit monitoring data of multiple models and types of satellites

Abstract

The invention discloses a method for quickly extracting on-orbit monitoring data of multiple models and types of satellites. The method comprises the following steps that 1, data extracting service connection between data extracting and processing software and an on-orbit monitoring data source is established, and the connection generally includes transmission control protocol/internet interconnection protocol data communication, user datagram protocol multicast data and the like. The method can have good applicability and universality, methods for extracting on-orbit monitoring data of satellites is normalized, the method can be used for guiding the design of software for extracting satellite on-orbit monitoring data and satellite testing data, the situation is changed that on-orbit monitoring data extracting modes of various models and types of satellites are different, the flexible and quick data extracting method makes application analysis of satellite on-orbit monitoring data moreconvenient and quicker, data extracting and processing software adopts browser/server frameworks, a computer provided with a browser can run without software installation, and the usability of the method is improved.

Description

technical field [0001] The invention relates to an extraction method, in particular to a rapid extraction method for multi-model and multi-type satellite on-orbit monitoring data. Background technique [0002] With the rapid development of the aerospace industry, the number of satellites in orbit continues to increase. After the satellite is launched, it will work in a complex space environment for a long time. It can only monitor and control its working status through the telemetry and remote control system. Data and other data information expands rapidly with time, and a large amount of accumulated test data and historical telemetry data contain valuable information, which can effectively reflect changes in the working mode and performance of satellites within a certain period of time, but they have not been effectively utilized. As a result, the current telemetry data analysis is facing the dilemma that it is difficult to mine value from a large amount of data, and even t...

AI Technical Summary

Problems solved by technology

[0002] With the rapid development of the aerospace industry, the number of satellites in orbit continues to increase. After the satellite is launched, it will work in a complex space environment for a long time. It can only monitor and control its working status through the telemetry and remote control system. Data and other data information expands rapidly with time, and a large amount of accumulated test data and historical telemetry data contain valuable information, which can effectively reflect changes in the working mode and performance of satellites within a certain period of time, but they have not been effectively utilized. As a result, the current telemetry data analysis is facing the dilemma that it is difficult to mine value from a large amount of data, and even though some commercial software can analyze data offline, it undoubtedly requires users to import data files every time they use it, and select the amount of data. , setting method, etc., the operation is time-consuming, and the method is poorly targeted, and specific analysis of specific telemetry data cannot be performed regularly. This design can be used to guide and standardize the extraction method of satellite in-orbit monitoring data, which is convenient for designers to quickly extract satellite-related data. data is used effectively

[0003] At present, the storage form of test data for on-orbit satellite models is not uniform, and the software for extracting on-orbit monitoring data is quite different among models. The software development work is redundant. There are huge differences in the extraction of on-orbit monitoring data for different types of satellites, and the extraction of satellite monitoring data is not flexible enough. , the result presentation methods are not diverse enough, which makes the analysis and application of on-orbit monitoring data more complicated, and cannot meet the application requirements of multi-model and multi-type satellite on-orbit monitoring data

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