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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Nonlinear filtering for sequential spacecraft attitude estimation with real data: Cubature Kalman Filter, Unscented Kalman Filter and Extended Kalman Filter

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Author(s):
Garcia, R. V. [1] ; Pardal, P. C. P. M. [1] ; Kuga, H. K. [2] ; Zanardi, M. C. [3]
Total Authors: 4
Affiliation:
[1] Univ Sao Paulo, EEL, Estr Municipal Campinho S-N, BR-12602810 Lorena, SP - Brazil
[2] Technol Inst Aeronaut, Praca Marechal Eduardo Gomes 50, BR-12228900 Sao Jose Dos Campos, SP - Brazil
[3] Fed Univ ABC, Ave Estados 5001, BR-09210580 Santo Andre, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: Advances in Space Research; v. 63, n. 2, p. 1038-1050, JAN 15 2019.
Web of Science Citations: 3
Abstract

This article compares the attitude estimated by nonlinear estimator Cubature Kalman Filter with results obtained by the Extended Kalman Filter and Unscented Kalman Filter. Currently these estimators are the subject of great interest in attitude estimation problems, however, mostly the Extended Kalman Filter has been applied to real problems of this nature. In order to evaluate the behavior of the Extended Kalman Filter, Unscented Kalman Filter and Cubature Kalman Filter algorithms when submitted to realistic situations, this paper uses real data of sensors on-board the CBERS-2 remote sensing satellite (China Brazil Earth Resources Satellite). It is observed that, for the case studied in this article, the filters are very competitive and present advantages and disadvantages that should be dealt with according to the requirements of the problem. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 18/04548-4 - Committee on Space Research - COSPAR 2018
Grantee:Roberta Veloso Garcia
Support Opportunities: Research Grants - Meeting - Abroad