Satellite telemetering data predicting method based on Kalman smoothing

Abstract

The invention relates to a satellite telemetering data predicting method based on Kalman smoothing. The satellite telemetering data predicting method based on Kalman smoothing solves the problems that the satellite telemetering data size is massive, the signal types are complicated, the requirements for the real-time performance, the consistency and the reliability of data are high, the data change rapidly along with the environment and a traditional manual data interpretation method can not meet the requirements of a satellite test. The telemetering data of the current moment of a satellite are used for predicting the telemetering data of the next moment in real time and abnormal changes of the data can be found in advance. In practical testing and applying, if the satellite telemetering data go abnormal, a certain telemetering value increases or decreases abnormally; at the initial stage, as the certain telemetering value does not exceed the preset threshold value, a tester can not find a test abnormality. By means of the data predicting method, the data of the next cycle can be accurately predicted, actions can be rapidly taken in terms of a zone with the abnormal data, the data abnormality can be found and predicted in time, and the tester is reminded to pay close attention to the data abnormality. In addition, the algorithm executing efficiency is high, the real-time performance requirement for the satellite test can be well met and the satellite telemetering data predicting method based on Kalman smoothing is suitable for long-term data interpretation and abnormal data detection.

Description

technical field [0001] The invention relates to a method for predicting satellite telemetry data based on Kalman filtering, and belongs to the technical field of satellite testing. Background technique [0002] Interpretation of satellite telemetry data refers to the process of conducting a correlation check on satellite control commands and downlink telemetry data during the comprehensive ground test process of the satellite, and judging whether the satellite equipment is working normally, whether the interface is correct, and whether the satellite is operating normally. In order to accurately grasp the working status of the satellite and find problems in time, testers must continuously monitor and interpret these data. [0003] At present, most of the satellite data interpretation work is still done by humans, which not only requires a large number of testers with rich knowledge and experience, but also has hidden dangers of missed and misjudged. The satellite test proces...

AI Technical Summary

Problems solved by technology

The amount of test data is huge, the types of signals are complex, the requirements for real-time data, consistency and reliability are high, and the data changes rapidly with the environment. Therefore, high requirements are placed on data interpretation and processing speed in satellite test systems. Traditional manual data interpretation methods Unable to meet satellite testing needs

In order to solve the above problems, the telemetry parameter automatic monitoring tool software is mainly used at present, which can automatically perform data interpretation according to the defined parameter range, and send an alarm prompt when the parameter exceeds the limit, but the definition of the abnormal range of the parameter is not precise enough, and it relies heavily on the experience of the tester

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