Far Ultraviolet Spectroscopic Explorer optical system: lessons learned

Details Far Ultraviolet Spectroscopic Explorer optical system: lessons learned Far Ultraviolet Spectroscopic Explorer optical system: lessons learned

Dec 2000

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000spie.4139..186c&link_type=abstract

Proc. SPIE Vol. 4139, p. 186-198, Instrumentation for UV/EUV Astronomy and Solar Missions, Silvano Fineschi; Clarence M. Korendy

Astronomy and Astrophysics

Astronomy

Scientific paper

The Far Ultraviolet Spectroscopic Explorer (FUSE) is a NASA astrophysics satellite designed to produce high resolution spectra in the far-ultraviolet (90.5-118.7 nm bandpass) with a high effective area (20-70 cm2) and low background detector. It was launched on a three-year mission in June 1999 aboard a Boeing Delta II rocket. The satellite has been performing routine science observations since December 1999. FUSE contains four co-aligned, normal incidence, off-axis parabolic primary mirrors which illuminate separate Rowland circle spectrograph channels equipped with holographically ruled diffraction gratings and microchannel plate detectors. Fine error sensors (slit jaw cameras) operating in the visible on two of the channels are used for target acquisition and guiding. The FUSE mission was first proposed in the late 1980s, and experienced several major conceptual changes prior to fabrication, assembly, and testing, which lasted from 1996 through 1999. During the program, we realized both positive and negative aspects to our design and processes that may apply to other space missions using telescopes and spectrographs. The specific topics we address are requirements, design, component specification, integration, and verification. We also discuss on-orbit alignment and focus. These activities were complicated by unexpected levels of motion between the optical elements, and the logistical problems associated with limited ground contact passes in low Earth orbit. We have developed methods to characterize the motions and mitigate their resultant effects on the science data through a combination of observing techniques and modifications to the data reduction software.

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