Batch and filter approaches to spacecraft sensor alignment estimation

Two Kalman-filter formulations are presented for the estimation of spacecraft sensor misalignments from inflight data. In the first the sensor misalignments are part of the filter state variable; in the second the state vector contains only dynamical variables, but the sensitivities of the filter innovations to the misalignments are calculated within the Kalman filter. This procedure permits the misalignments to be estimated in batch mode as well as a much smaller dimension for the Kalman filter state vector. This results not only in a significantly smaller computational burden but also in a smaller sensitivity of the misalignment estimates to outliers in the data. Numerical simulations of the filter performance are presented.

The QUEST for Brazilian space research

This paper describes how QUEST 1 (QUaternion ESTimator algorithm) influenced Brazilian space research activities. Indeed, we present a short survey paper on researches in attitude determination and propagation in Brazil arising from the influence of the author of QUEST. We show how Brazilian researchers started implementing QUEST, tasting it, and later deriving other applications based on it. Some Brazilian researchers worked out further investigations through direct interaction with the QUEST author, Dr. Malcolm Shuster, addressing attitude alignment and calibration problems. Further related researches show the influence of Dr. Shuster's work on Brazilian space research.