This paper discusses the Instrument Pointing Frame (IPF) Kalman Filter algorithm for focal plane calibration of NASA's Space Infrared Telescope Facility (SIRTF). The IPF Kalman filter is a high-order square-root iterated linearized Kalman filter, which is parametrized specifically for calibrating the SI RTF telescope focal plane and aligning the science instrument arrays with respect to the telescope boresight. The most stringent calibration requirement specifies the alignment of certain instrument pointing frames to an accuracy of 0.1 arcseconds, per-axis, 1-sigma relative to the telescope pointing frame [IO]. In order to achieve this level of accuracy, the IPF filter requires 37 states to estimate desired parameters while also correcting for expected systematic errors due to: (1) optical distortions, (2) scanning mirror scale-factor and misalignment, (3) frame alignment variations due to thermomechanical distortion, and (4) gyro bias and bias-drift in all axes. The estimated pointing frames and calibration parameters are essential for supporting onboard precision pointing capability, in addition to supporting end-to-end "pixels on the sky" ground pointing reconstruction efforts.
This paper addresses an estimation problem specific to formation flying of spacecraft that can be approached with rule or logic based methodologies. A decentralized and self-centered framework of the estimator is formulated and shown to be a feasible estimation architecture under formation reconfiguration or formation member failures. A rule-based strategy is applied to the problem that switches the gain of the linear observer of the formation. Each gain set is derived from a constant gain linear observer optimized for either formation member acquisition or steady state operation. The formation member acquisition time can be critical when considering a dynamic formation reconfiguration followed by precision pointing required by scientific mission. This particular strategy has the advantages of onboard computational efficiency and fast Alter convergence during formation initialization or formation member acquisition. A two-spacecraft simulation analysis was performed to demonstrate and validate the efficacy of the algorithm.
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