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Multiple Robust High-degree Cubature Kalman Filter for Relative Position and Attitude Estimation of Satellite Formation.
- Source :
-
Journal of Navigation . Sep2019, Vol. 72 Issue 5, p1254-1274. 21p. - Publication Year :
- 2019
-
Abstract
- The High-degree Cubature Kalman Filter (HCKF) is proposed as a novel methodology based on the arbitrary degree spherical rule, which can achieve better performance than the traditional Kalman filter. However, it also has a large calculation burden when used in a high-dimension and high-degree of accuracy estimation system. The number of sampling points of an HCKF increases polynomially with increasing state-space dimensions, which further increases the calculation burden. The reduction of the number of the state-space dimensions is the main contribution of this study. A strategy for HCKF based on the partitioning of the state-space and orthogonal principle is introduced, referred to as the Multiple Robust HCKF (MRHCKF). It is shown that this technique can effectively reduce the calculation burden for the high-dimension system with robust performance. Numerical simulations are performed for the example of high-dimension relative position and attitude estimation to show that the proposed method can obtain nearly the same performance as the HCKF, while drastically reducing computational complexity. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03734633
- Volume :
- 72
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Journal of Navigation
- Publication Type :
- Academic Journal
- Accession number :
- 138013402
- Full Text :
- https://doi.org/10.1017/S0373463319000079