TY - JOUR
T1 - Robust filtering for spacecraft attitude estimation systems with multiplicative noises, unknown measurement disturbances and correlated noises
AU - Chu, Shuai
AU - Qian, Huaming
AU - Sreeram, Victor
N1 - Funding Information:
This work was co-supported by the Area Research and Development Program of Guangdong Province (No. 2020B0909020001) and the National Natural Science Foundation of China (No. 61573113).
Publisher Copyright:
© 2023
PY - 2023/11/1
Y1 - 2023/11/1
N2 - Unknown measurement disturbances and correlated noise caused by jitter or vibration phenomena during spacecraft operation and the complex external environment are important topics for spacecraft attitude estimation. This paper studies the problem of spacecraft attitude estimation for nonlinear systems with multiplicative noises, unknown measurement disturbances and correlated noises. In addition, a two-step prediction framework is used to complete the noise decoupling. This paper aims to design a robust filter that minimizes the upper bound of the prediction error covariance and estimation error covariance in the presence of multiplicative noises, correlated noises and unknown measurement disturbances. The prediction gain and filtering gain of the robust filter are designed to minimize the upper bound. Finally, the simulation results verify the effectiveness of the proposed filter.
AB - Unknown measurement disturbances and correlated noise caused by jitter or vibration phenomena during spacecraft operation and the complex external environment are important topics for spacecraft attitude estimation. This paper studies the problem of spacecraft attitude estimation for nonlinear systems with multiplicative noises, unknown measurement disturbances and correlated noises. In addition, a two-step prediction framework is used to complete the noise decoupling. This paper aims to design a robust filter that minimizes the upper bound of the prediction error covariance and estimation error covariance in the presence of multiplicative noises, correlated noises and unknown measurement disturbances. The prediction gain and filtering gain of the robust filter are designed to minimize the upper bound. Finally, the simulation results verify the effectiveness of the proposed filter.
KW - Correlated noise
KW - Kalman filter
KW - Multiplicative noise
KW - Robust filter
KW - Unknown measurement disturbance
UR - http://www.scopus.com/inward/record.url?scp=85165713473&partnerID=8YFLogxK
U2 - 10.1016/j.asr.2023.07.008
DO - 10.1016/j.asr.2023.07.008
M3 - Article
AN - SCOPUS:85165713473
SN - 0273-1177
VL - 72
SP - 3619
EP - 3630
JO - Advances in Space Research
JF - Advances in Space Research
IS - 9
ER -