Abstract
The differential geometric filter is implemented to estimate the absolute and relative positions of the spacecraft in a formation. The extended Kalman Filter is also implemented as a benchmark for the differential geometric estimation. Only relative positions between the spacecraft are measured. Relative positions are measured using a wireless local positioning system (WLPS) installed in all spacecraft. Two different scenarios are studied: (1) the observations include WLPS measurements only and (2) the observations include WLPS measurements in addition to measurements for the absolute position of one spacecraft made by a radar that takes measurements from the earth’s surface. Results show that the differential geometric estimation has better stability performance and a faster convergence rate compared to the extended Kalman filter.
Highlights
The relative and absolute positions estimation of spacecraft formations is a fundamental task in many space missions
Relative position estimation plays an important role in Spacecraft Formation Flying (SFF) missions, a subject that has been the focus of many researches during last decade
The convergence rate is determined by the amount of time required by the estimator’s root mean square error (RMSE) to fall within a RMSE threshold, ethres
Summary
The relative and absolute positions estimation of spacecraft formations is a fundamental task in many space missions. Relative positions between satellites, such as Cluster and Cluster-II satellites launched by the European Space Agency, are estimated and controlled to support many collaborative tasks where satellites are required to maintain a specific formation in a continuous manner within the mission period [2]. A GPS-like technology that can be applied to SFF have been introduced [3, 4], where each spacecraft is equipped with a communication system to localize other spacecraft in the formation. This system provides high precision estimates for relative positions. This system does not stand alone and requires a GPS system
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