Comparison of Statistical Estimation Techniques for Mars Entry, Descent and Landing Reconstruction from MEDLI-like Data Sources
Author(s) -
Soumyo Dutta,
Robert D. Braun,
Ryan Russell,
Ian G. Clark,
Scott A. Striepe
Publication year - 2012
Publication title -
50th aiaa aerospace sciences meeting including the new horizons forum and aerospace exposition
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2012-400
Subject(s) - mars exploration program , descent (aeronautics) , computer science , artificial intelligence , astrobiology , aerospace engineering , engineering , physics
Flight data from an entry, descent, and landing (EDL) sequence can be used to reconstruct the vehicle's trajectory, aerodynamic coefficients and the atmospheric profile experienced by the vehicle. Past Mars missions have contained instruments that do not provide direct measurement of the freestream atmospheric conditions. Thus, the uncertainties in the atmospheric reconstruction and the aerodynamic database knowledge could not be separated. The upcoming Mars Science Laboratory (MSL) will take measurements of the pressure distribution on the aeroshell forebody during entry and will allow freestream atmospheric conditions to be partially observable. This data provides a mean to separate atmospheric and aerodynamic uncertainties and is part of the MSL EDL Instrumentation (MEDLI) project. Methods to estimate the flight performance statistically using on-board measurements are demonstrated here through the use of simulated Mars data. Different statistical estimators are used to demonstrate which estimator best quantifies the uncertainties in the flight parameters. The techniques demonstrated herein are planned for application to the MSL flight dataset after the spacecraft lands on Mars in August 2012.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom