ADVANCED 3D SENSING ALGORITHMS AND COMPUTER ARCHITECTURES FOR SIMULTANEOUS MAPPING AND CLOSE PROXIMITY OPERATIONS
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Sensing algorithms and computational architectures play an important role in the simultaneous location, mapping and close proximity operations of spacecraft. Along with an error characterization of the relative motion states, a sensor fusion method is proposed in this paper that utilizes a double bootstrapping approach to perform real time computation of measurement error statistics. A generalized QUEST model is discussed that includes the translation vector in the close proximity navigation measurements. Based on the generalized QUEST measurement model, a multiplicative extended Kalman filter is proposed to estimate the relative motion states between the vehicles of interest. It is shown that this technique can be used to estimate the full attitude and relative motion translation states even at modest sampling rates. A sensitivity analysis is performed to identify the observable state estimation error accuracies. Copyright © 2013 by The Charles Stark Draper Laboratory, Inc.
author list (cited authors)
Majji, M., & Junkins, J. L.