Space Mission Scheduling Toolkit for Long-Term Deep Space Network Loading Analyses and Strategic Planning
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/169524
Realitzat a/ambJet Propulsion Laboratory
Tipus de documentTreball Final de Grau
Data2019-07-16
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
:
Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
The Jet Propulsion Laboratory (JPL) owns and operates the Deep Space Network (DSN), a set of antennas placed around Earth to communicate with spacecraft flying anywhere in the Solar System. While the DSN is a critical asset to JPL and NASA's success, it is also expensive to build, maintain and operate. Therefore, additional system capabilities are planned strategically, years in advance, by forecasting which missions will utilize the system in the coming decades (and their driving data requirements). Then, loading analyses are conducted assuming different scenarios, each one simulating DSN operations for several years.
Within this context, this thesis focuses on developing an automated long-term scheduling mechanism that can mimic real DSN operations. Several factors are modeled and accounted for in this process: Spacecraft visibility constraints, evolution of the DSN architecture, characteristics of each antenna, as well as link and other operational constraints.
To implement the scheduling mechanisms, several options are first identified and downselected. Then, it is explained in detail how the automated long-term scheduling toolkit –LTST– formulates the problem as a mixed
TitulacióGRAU EN ENGINYERIA EN TECNOLOGIES AEROESPACIALS/GRAU EN ENGINYERIA INFORMÀTICA
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
Bachelor Thesis - Guillem Rueda Oller.pdf | 1,927Mb | Visualitza/Obre |