Symplectic Attitude Estimation for Small Satellites
SURREY UNIV GUILDFORD (UNITED KINGDOM)
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In this paper, a novel method for efficient high-accuracy satellite attitude estimation is presented. Symplectic numerical methods are applied to the Extended Kalman Filter EKF algorithm to give the SKF, which outperforms the standard EKF in the presence of nonlinearity and low measurement noise in the 1-D case. Building on this result, a six-state SKF is compared to an EKF of the same order for satellite attitude estimation. Simulation of a standard small satellite mission demonstrates orders of magnitude improvement in state accuracy and preservation of constants of motion. This new method shows promise for improved attitude estimation onboard resource-constrained small satellites.
- Numerical Mathematics