دانلود مقاله ISI انگلیسی شماره 147283
ترجمه فارسی عنوان مقاله

فیلتر کلمن فیلتر کوباتی قابل تنظیم برای برآورد نگرش ماهواره ای

عنوان انگلیسی
Adaptive robust cubature Kalman filtering for satellite attitude estimation
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
147283 2018 14 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Chinese Journal of Aeronautics, Volume 31, Issue 4, April 2018, Pages 806-819

ترجمه کلمات کلیدی
برآورد نگرش، فیلتر کوباتور کالمن، عوامل مؤثر چندگانه، فاکتور سازگاری بهینه، فیلترشکن قوی
کلمات کلیدی انگلیسی
Attitude estimation; Cubature Kalman filter; Multiple fading factors; Optimal adaptive factor; Robust filtering;
پیش نمایش مقاله
پیش نمایش مقاله  فیلتر کلمن فیلتر کوباتی قابل تنظیم برای برآورد نگرش ماهواره ای

چکیده انگلیسی

This paper is concerned with the adaptive robust cubature Kalman filtering problem for the case that the dynamics model error and the measurement model error exist simultaneously in the satellite attitude estimation system. By using Hubel-based robust filtering methodology to correct the measurement covariance formulation of cubature Kalman filter, the proposed filtering algorithm could effectively suppress the measurement model error. To further enhance this effect and reduce the impact of the dynamics model error, two different adaptively robust filtering algorithms, one with the optimal adaptive factor based on the estimated covariance matrix of the predicted residuals and the other with multiple fading factors based on strong tracking algorithm, are developed and applied for the satellite attitude estimation. The quaternion is employed to represent the global attitude parameter, and three-dimensional generalized Rodrigues parameters are introduced to define the local attitude error. A multiplicative quaternion error is derived from the local attitude error to maintain quaternion normalization constraint in the filter. Simulation results indicate that the proposed novel algorithm could exhibit higher accuracy and faster convergence compared with the multiplicative extended Kalman filter, the unscented quaternion estimator, and the adaptive robust unscented Kalman filter.