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Comparison of Statistical Estimation Techniques for Mars Entry, Descent, and Landing Reconstruction from MEDLI-like Data Sources

机译:从类似MEDLI的数据源进行火星进入,下降和着陆重建的统计估计技术的比较

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摘要

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.
机译:来自进入,下降和着陆(EDL)序列的飞行数据可用于重建车辆的轨迹,空气动力学系数和车辆所经历的大气廓线。过去的火星任务所包含的仪器无法直接测量自由流的大气状况。因此,大气重建和空气动力学数据库知识的不确定性无法分离。即将到来的火星科学实验室(MSL)将在进入过程中对机壳前体上的压力分布进行测量,并允许部分观察自由流大气条件。此数据提供了分离大气和空气动力学不确定性的手段,并且是MSL EDL Instrumentation(MEDLI)项目的一部分。本文通过使用模拟火星数据演示了使用机载测量值统计地评估飞行性能的方法。使用不同的统计估计量来证明哪个估计量可以最好地量化飞行参数中的不确定性。计划在2012年8月航天器降落在火星上之后,将本文演示的技术应用于MSL飞行数据集。

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