Consistent Estimation of Spacecraft Sensor Alignments

Abstract

Simple and statistically correct algorithms are developed for batch estimation of spacecraft sensor alignments from pre-launch and inflight data without the need to compute the spacecraft attitude or angular velocity. These algorithms permit the estimation of sensor alignments in a framework free of unknown dynamical variables. In actual mission implementation, algorithms such as those presented here are usualy better behaved and more efficient than those which must compute sensor alignments simultaneously with the spacecraft attitude, say, by means of a Kalman filter. In particular, these algorithms are less sensitive to data dropouts of long duration, and the derived measurements used in the attitude-independent algorithm usually make data checking and editing of outliers much simpler than would be the case in the filter. An estimator for the launch-shock error levels is also developed and the effect of unobservable launch shock on the misalignment estimates is studied. The algorithms are applied to a realistic simulated example which approximates actual missions.