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Maneuvering Spacecraft Tracking via State-Dependent Adaptive Estimation
Maneuvering Spacecraft Tracking via State-Dependent Adaptive Estimation
Introduction
Introduction
In this study, an adaptive estimation algorithm is developed to estimate the state of a spacecraft that performs impulsive maneuvers. The accurate tracking of a maneuvering spacecraft with impulsive burns is a challenging problem since the magnitude and the time of occurrence of impulsive maneuvers are usually unknown a priori.
Impulsive maneuver from a GTO to a GEO at apogee with uncertainty
Stochastic Dynamical System subject to Abrupt State Jumps: Modeling and State-Dependent Adaptive Estimation
Stochastic Dynamical System subject to Abrupt State Jumps: Modeling and State-Dependent Adaptive Estimation
To deal with this problem, an adaptive state estimation algorithm is developed in this study using a bank of extended Kalman filters (EKFs) along with interacting multiple models (IMM) that account for spacecraft motion with and without impulsive maneuvers.
Motivated by the fact that impulsive maneuvers usually occur when certain conditions on the spacecraft state are satisfied, the multiple extended Kalman filters (EKFs) are systematically blended using a state-dependent transition probability.
Since the information about the conditions based on which impulsive maneuvers occur is explicitly used in the state-dependent transition probability, the proposed algorithm can predict the impulsive maneuvers more accurately and thus produce more accurate state estimates.
Structure of the proposed algorithm
Applications to Tracking of Impulsively Maneuvering Spacecraft
Applications to Tracking of Impulsively Maneuvering Spacecraft
The proposed algorithm is demonstrated with two illustrative examples:
Example 1: Tracking of Geostationary Satellite Performing Station-Keeping Maneuvers
Example 1: Tracking of Geostationary Satellite Performing Station-Keeping Maneuvers
A true trajectory of the geostationary satellite in the y − z plane of the Local Vertical and Local Horizontal (LVLH) frame (corresponding to longitude–latitude)
History of the inclination of the geostationary satellite around the moment of a North-South (NS) station-keeping maneuver.
Comparison of state estimation accuracy (100 Monte Carlo runs).
Example 2: Tracking of Spacecraft Performing Orbital Transfers
Example 2: Tracking of Spacecraft Performing Orbital Transfers
Impulsive maneuver at a node for a noncoplanar transfer (inclination change)
A true trajectory of the spacecraft around its ascending node
Comparison of state estimation accuracy (100 Monte Carlo runs): RMS position error (left) and RMS velocity error (right)
Related Publication
Related Publication
S. Lee, J. Lee, and I. Hwang, “Maneuvering Spacecraft Tracking via State-Dependent Adaptive Estimation,” AIAA Journal of Guidance, Control and Dynamics, Vol.39(9), pp.2034-2043, September 2016, DOI: 10.2514/1.G001567
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