Spacecraft alignment estimation

Abstract

A numerically well-behaved factorized methodology is developed for estimating spacecraft sensor alignments from prelaunch and inflight data without the need to compute the spacecraft attitude or angular velocity. Such a methodology permits the estimation of sensor alignments (or other biases) in a framework free of unknown dynamical variables. In actual mission implementation such an algorithm is usually better behaved than one that must compute sensor alignments simultaneously with the spacecraft attitude, for example by means of a Kalman filter. In particular, such a methodology is less sensitive to data dropouts of long duration, and the derived measurement used in the attitude-independent algorithm usually makes data checking and editing of outliers much simpler than would be the case in the filter.