Application of decision tree regression in navigation satellite telemetry data modeling

Xuehuan Zhang; Jianwei Sun; Daiyan Zhao

doi:10.1117/12.2653511

8 December 2022 Application of decision tree regression in navigation satellite telemetry data modeling

Xuehuan Zhang, Jianwei Sun, Daiyan Zhao

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124741D (2022) https://doi.org/10.1117/12.2653511
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

In order to understand the working state of on orbit satellites, it is necessary to analyze the telemetry data. The fast-changing telemetry data is an important data to express the navigation service status of navigation satellite. Its analysis and modeling are helpful to mine the deep information of navigation telemetry data. A modeling method of on orbit navigation satellite fast-changing telemetry data based on decision tree regression is proposed. The model is used to predict the power measurements at frequency points. The results show that R2 value is greater than 0.96, and the error of prediction value is small. A fast-changing telemetry data model with good effect is established, which provides a possible scheme for the application of artificial intelligence in the analysis of fast-changing telemetry data.

Citation Download Citation

Xuehuan Zhang, Jianwei Sun, and Daiyan Zhao "Application of decision tree regression in navigation satellite telemetry data modeling", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124741D (8 December 2022); https://doi.org/10.1117/12.2653511

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