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Proceedings Paper

Neural-network-based satellite tracking for deep space applications
Author(s): Farid Amoozegar; Charles Ruggier
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Paper Abstract

NASA has been considering the use of Ka-band for deep space missions primarily for downlink telemetry applications. At such high frequencies, although the link will be expected to improve by a factor of four, the current Deep Space Network (DSN) antennas and transmitters would become less efficient due to higher equipment noise figures and antenna surface errors. Furthermore, the weather effect at Ka-band frequencies will dominate the degradations in link performance and tracking accuracy. At the lower frequencies, such as X-band, conventional CONSCAN or Monopulse tracking techniques can be used without much complexity, however, when utilizing Ka-band frequencies, the tracking of a spacecraft in deep space presents additional challenges. The objective of this paper is to provide a survey of neural network trends as applied to the tracking of spacecrafts in deep space at Ka-band under various weather conditions, and examine the trade-off between tracking accuracy and communication link performance.

Paper Details

Date Published: 16 September 2003
PDF: 17 pages
Proc. SPIE 5094, Automatic Target Recognition XIII, (16 September 2003); doi: 10.1117/12.488688
Show Author Affiliations
Farid Amoozegar, Jet Propulsion Lab. (United States)
Charles Ruggier, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 5094:
Automatic Target Recognition XIII
Firooz A. Sadjadi, Editor(s)

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