Abstract

A statistical method was developed for modeling the large space debris motion in the class of autoregressive models. The method improves the quality of description and forecasting of the movement of large fragments of space debris based on their TLE elements.

Highlights

  • Technogenic pollution on low earth orbits level is an urgent problem of modern astronautics

  • This distinctive feature of the TLE-element time series is used to modify the parameter estimation procedures when constructing autoregressive models of large space debris motion [1]. To model this kind of time series, an iterative procedure for the parametric identification of autoregressive models with unequally spaced observations was developed, the effectiveness of which was confirmed by the method of statistical tests

  • In certain time series intervals, the model errors take on values that significantly exceed the values from the ranges given

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Summary

Introduction

Technogenic pollution on low earth orbits level is an urgent problem of modern astronautics. Major part 1 A method for modeling of large space debris motion in the class of autoregressive models using their TLE elements Determination of the order and estimation of the coefficients of autoregressive models in conditions of structural uncertainty by the number and composition of regressors is an urgent problem of the theory of identification, and there are various approaches to its solution. This distinctive feature of the TLE-element time series is used to modify the parameter estimation procedures when constructing autoregressive models of large space debris motion [1]. To model this kind of time series, an iterative procedure for the parametric identification of autoregressive models with unequally spaced observations was developed, the effectiveness of which was confirmed by the method of statistical tests.

The time interval between the current and the previous observation
Root mean square errors of models for spacecraft and spent stages
Conclusion
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