Paper
18 August 2005 Network compensation of optical metrology for satellite formation flying
Author Affiliations +
Abstract
The metrology of a satellite formation is a system-level issue relying on the measurement technology, number and selection of metrology links, location and tolerances of the components used to materialize the optical paths, and a variety of issues related to redundancy, recovery from contingencies, failure modes and sensor degradation. For a complex interferometric system such as ESA/Darwin, metrology must provide distances, angles and decide the right moments to "rigidify" the configuration and to keep it stable within small limits. Multi-stage approaches can be used, with GPS-like sensors, absolute or relative distance / angle sensors, fringe sensors, heterodyne interferometers. Each type of sensors is materialized by several devices with different accuracies, biases, degradation constants. In this paper, we demonstrate the applicability of geodetic compensation of the metrological network to refine the instantaneous knowledge of the constellation configuration - modelled as a network of nodes - by providing confidence regions for the location of nodes with smaller uncertainties, and pinpointing how better estimations of the internal calibration parameters can be obtained. In such framework, the following can be, in principle, analyzed: impact of the number and distribution of metrological links, added value of a link and its level of correlation with others, uncertainty reduction by network compensation, effects of redundant links and/or links with different accuracies on final accuracy and impact of sensor temporal degradation.
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Paulo Jorge Motrena, Jose Manuel Rebordao, and Alexandre Pereira Cabral "Network compensation of optical metrology for satellite formation flying", Proc. SPIE 5879, Recent Developments in Traceable Dimensional Measurements III, 58790P (18 August 2005); https://doi.org/10.1117/12.613652
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KEYWORDS
Satellites

Metrology

Distance measurement

Sensors

Mathematical modeling

Error analysis

Stochastic processes

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