Physics
Scientific paper
Nov 1994
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994smog.symp..311s&link_type=abstract
In NASA. Goddard Space Flight Center, Third International Symposium on Space Mission Operations and Ground Data Systems, Part 1
Physics
Deep Space Network, Earth Orbital Environments, Satellite Communication, Satellite Networks, Satellite Tracking, Tdr Satellites, Challenger (Orbiter), Forecasting, Hubble Space Telescope, Nasa Programs, Space Shuttle Mission 51-L
Scientific paper
This paper reviews Space Network (SN) demand forecasting experience over the past 16 years and describes methods used in the forecasts. The paper focuses on the Single Access (SA) service, the most sought-after resource in the Space Network. Of the ten years of actual demand data available, only the last five years (1989 to 1993) were considered predictive due to the extensive impact of the Challenger accident of 1986. NASA's Space Network provides tracking and communications services to user spacecraft such as the Shuttle and the Hubble Space Telescope. Forecasting the customer requirements is essential to planning network resources and to establishing service commitments to future customers. The lead time to procure Tracking and Data Relay Satellites (TDRS's) requires demand forecasts ten years in the future a planning horizon beyond the funding commitments for missions to be supported. The long range forecasts are shown to have had a bias toward underestimation in the 1991 -1992 period. The trend of underestimation can be expected to be replaced by overestimation for a number of years starting with 1998. At that time demand from new missions slated for launch will be larger than the demand from ongoing missions, making the potential for delay the dominant factor. If the new missions appear as scheduled, the forecasts are likely to be moderately underestimated. The SN commitment to meet the negotiated customer's requirements calls for conservatism in the forecasting. Modification of the forecasting procedure to account for a delay bias is, therefore, not advised. Fine tuning the mission model to more accurately reflect the current actual demand is recommended as it may marginally improve the first year forecasting.
Levine Allen J.
Pitt Karl J.
Stern Daniel C.
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