System verification of the JMEX mission residual motion requirements with integrated modeling

Details System verification of the JMEX mission residual motion requirements with integrated modeling System verification of the JMEX mission residual motion requirements with integrated modeling

Aug 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005spie.5899....1l&link_type=abstract

UV/Optical/IR Space Telescopes: Innovative Technologies and Concepts II. Edited by MacEwen, Howard A. Proceedings of the SPI

Computer Science

Performance

Scientific paper

The Jupiter Magnetospheric Explorer (JMEX) is a UV observatory operating in an earth orbit proposed as part of NASA's Small Explorer (SMEX) class of missions. To meet mission requirements the residual jitter portion of the imaging error budget is set at 0.079 arcsec (3σ) over a 33.3 ms frame integration time and 0.01 arcsec (3σ) for all frequency content higher than 15 Hz. These requirements are challenging for a small, low cost mission and require some innovative system solutions to achieve these goals. The solution, discussed in the paper, was to combine several jitter rejection techniques fine-balanced reaction wheel mounted on an isolation assembly, post processing using science images and reaction wheel momentum control. This paper focuses primarily on meeting the high frequency portion of the requirements. To facilitate system performance verification, we leveraged an integrated model toolset, EOSyM (End-to-end Optical System Model), developed and used on various other advanced space-based missions over the last 9 years. Starting with individual subsystem models for the reaction wheel disturbances, the coupled payload/ spacecraft structural dynamics model, and the optical design, we were able to evaluate the end-to-end LOS performance under varying reaction wheel speeds. At the end we found that the requirements could be met by maintaining the reaction wheels operating range within a well-defined speed band. This paper describes the mission, the technical challenges, the integrated model, and system performance results.

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