Filtragem robusta de trajetórias de veículos espaciais.

Abstract

In this work, a new methodology of filtering data of paths of space vehicles is proposed H2 and H∞ saw state estimates and discreet. In that new methodology, it is obtained, initially, the solution of the problem of filtering of data of paths of space vehicles saw state estimate through the equations of the filter of Kalman for Predicted Estimators and Filtered Estimators. The problem is solved through the mathematical development of the equations of the filter of Kalman that has as main function, to find a state estimate that minimizes the least-squares error. The equations mathematics are used for the development of the algorithm of the filter of Kalman. The algorithm of filtering of Kalman has two basic functions: prediction and correction. In the prediction phase the initial estimates and updating of the time of sampling are given, while, in the correction phase they are updated the measures. It is applied, also, the new methodology proposed in the project of filtering of data of path of space vehicles H∞ saw state estimate through equations of robust filter. The robust filtering has as function to esteem a linear combination that minimizes the norm, that has the interpretation of the existence of earnings of maximum energy of the entrance for the exit. In addition, it is obtained a new algorithm for filtering of data of paths of space vehicles, now through state estimate. All the project procedures are cultured through some applied examples to systems of tracking of space vehicles. The results are compared and discussed.