Figure: A typical view of the Planning Tool. Original PostScript figure (1.4MB).
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S. E. Paswaters, D. Wang
Interferometrics Inc. 14120 Parke Long Court, Chantilly, VA 22021,
E-mail: scott@argus.nrl.navy.mil
R. A. Howard
Naval Research Laboratory, 4555 Overlook Ave. SW, Washington DC, 20375
The Planning Tool allows users to develop customized observing sequences while monitoring compression factors and on-board processing times to realistically work within the limits of the instruments. The Scheduling Tool then graphically displays scheduled sequences and highlights potential resource conflicts. Sequences are saved in database tables as ``as planned observations'' and are available to be retrieved at any later date. Outputs include: database updates, inputs to the SOHO science activity plan, and the command loads themselves. Statistics are gathered after the images are received so the tool is constantly improving its estimate of processing time and compression factor.
The LASCO (Large Angle Spectrometric Coronagraph) / EIT (Extreme Ultraviolet Imaging Telescope) instrument packages having been operating continuously since shortly after launch of the SOHO (Solar and Heliospheric Observatory) satellite on December 2, 1995. SOHO is located at the Lagrangian L1 point providing uninterrupted observations of the sun. Commanding and data acquisition are performed in real time eight hours of every day with the remaining time provided through solid-state recorder dumps (see Wang et al. 1997, for more on the LASCO data archive). Observation schedules are uplinked daily, consisting of a baseline long-range synoptic program as well as specific observations to take advantage of changing targets on the sun, special science programs, or joint observations with other observatories. The LASCO/EIT electronics are extremely flexible, offering various image compression techniques which are traded off with consideration of scientific goals. The Planning Tool (Figure 1) allows users to develop customized observing sequences while monitoring compression factors and on-board processing times to work realistically within the limits of the instruments. The Scheduling Tool (Figure 2) then graphically displays scheduled sequences and highlights potential resource conflicts. The user can easily add, remove, or modify these sequences.
Figure: A typical view of the Planning Tool.
Original PostScript figure (1.4MB).
Figure: A typical view of the Scheduling Tool.
Original PostScript figure (1.7MB).
The Planning and Scheduling Tool is written in IDL (~12,000 lines of code) with a call to a C routine to generate the binary command strings. The tool is coupled with a relational database (Esfandiari, Paswaters, & Wang 1997) to archive observing sequences and maintain statistics (compression factor, processing time) of science images. Observing sequences are scheduled to maximize the use of LASCO/EIT science telemetry resources (5kBs-1/60MBday-1 compressed science data) while monitoring on-board processing time to avoid over-scheduling.
Table: width 0pt height 2.5ex depth 3ex
Sample ``As Planned Observations'' Summary.
A summary of ``as planned observations'' is output as an ASCII readable file providing a top level view of the schedule (Table 12).
A SOHO science activity plan file is generated summarizing LASCO's upcoming observations for SOHO-wide planning. Binary formatted commands are output into a single command file. Typical daily command loads consist of 300-500 commands. Consistency checks are performed on this file, and then the commands are uplinked through a separate piece of software from a LASCO workstation at GSFC to the instrument.
The Planning and Scheduling Tool is currently being used almost exclusively for commanding the LASCO and EIT instruments. Integrating user's customized observing sequences with the overall synoptic program typically takes on the order of half an hour, thus reducing the burden on the operations staff. Through the use of unique observing sequence numbers, users can correlate their planned observations with the actual data through database queries, and recall specific observations sequences to modify or run in the future.
Esfandiari, A. E., Paswaters, S. E., & Wang, D. 1997, this volume
Wang, D., Howard, R. A., Paswaters, S. E., Esfandiari, A. E., & Rich, N. 1997, this volume
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