Monte Carlo analysis of Titan/transfer orbit stage planetary mission guidance system

Details Monte Carlo analysis of Titan/transfer orbit stage planetary mission guidance system Monte Carlo analysis of Titan/transfer orbit stage planetary mission guidance system

Jan 1995

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1995jgcd...18..121b&link_type=abstract

Journal of Guidance, Control, and Dynamics (ISSN 0731-5090), vol. 18, no. 1, p. 121-127

Statistics

Computation

1

Interplanetary Flight, Mars Observer, Orbit Insertion, Space Missions, Spacecraft Guidance, Titan 3 Launch Vehicle, Trajectory Analysis, Transfer Orbits, Interim Stages (Spacecraft), Mathematical Models, Mission Planning, Monte Carlo Method, Optimization, Parameter Identification, Polynomials

Scientific paper

An important part of space launch vehicle mission planning for a planetary mission is the integrated analysis of guidance and performance dispersions for both booster and upper stage vehicles. For the Mars Observer mission, an integrated trajectory analysis was used to maximize the scientific payload and minimize injection errors by optimizing the energy management of both vehicles. This was accomplished by designing the Titan 3 booster vehicle to inject into a transfer orbit plane and the transfer orbit stage (TOS) to correct any booster dispersions. An integrated Monte Carlo analysis of the performance and guidance dispersions of both vehicles provided sensitivities and a statistical evaluation of their guidance schemes. The polynomial guidance schemes used for the Titan 3 variable flight azimuth computations and the TOS solid rocket motor ignition time and burn direction derivations accounted for a wide variation of launch times, performance dispersions, and target conditions. The Titan 3/TOS vehicle, which launched the Mars Observer spacecraft on Sept. 25, 1992, used these polynomial schemes. The postflight analysis indicated that a near perfect park orbit injection was achieved, followed by a hyperbolic orbit injection with less than 2 sigma errors.

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