Tech Briefs

Covariance Analysis of Astrometric Alignment Estimation Architectures for Precision Dual-Spacecraft Formation Flying

A paper highlights analysis of proposed navigation systems and architectures for achieving precise dual-spacecraft astrometric alignment. The dynamics of dual-spacecraft relative motion, within a restricted n-body problem framework, are shown to reduce to a simple linear form for use in estimation filter design and error analysis for a deep space mission application, such as MASSIM (Milli-Arc-Second Structure Imager). This model is augmented with simplified measurement process models of relevant measurement types. These include inertial sensors, such as accelerometers and rate gyros, as well as optical alignment sensors, such as star and laser beacon trackers. A consider-state covariance analysis tool is developed from these process models and used to study the performance of proposed estimation architectures for the MASSIM application. This work develops a generic analysis methodology for evaluation of dual-spacecraft relative navigation systems and architectures for precise dual-spacecraft astrometric alignment.

This work was done by Neerav Shah and Philip Calhoun of Goddard Space Flight Center. GSC-16726-1

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