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Planetary Probe Entry Atmosphere Estimation Using Synthetic Air Data System

机译:利用合成空气数据系统估算行星探测器进入大气

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This paper develops an atmospheric state estimator based on inertial acceleration and angular rate measurements combined with an assumed vehicle aerodynamic model. The approach utilizes the full navigation state of the vehicle (position, velocity, and attitude) to recast the vehicle aerodynamic model to be a function solely of the atmospheric state (density, pressure, and winds). Force and moment measurements are based on vehicle sensed accelerations and angular rates. These measurements are combined with an aerodynamic model and a Kalman-Schmidt filter to estimate the atmospheric conditions. The new method is applied to data from the Mars Science Laboratory mission, which landed the Curiosity rover on the surface of Mars in August 2012. The results of the new estimation algorithm are compared with results from a Flush Air Data Sensing algorithm based on onboard pressure measurements on the vehicle forebody. The comparison indicates that the new proposed estimation method provides estimates consistent with the air data measurements, without the use of pressure measurements. Implications for future missions such as the Mars 2020 entry capsule are described.
机译:本文基于惯性加速度和角速率测量,并结合假设的车辆空气动力学模型,开发了一种大气状态估计器。该方法利用了车辆的完整导航状态(位置,速度和姿态)来将车辆空气动力学模型改写为仅是大气状态(密度,压力和风)的函数。力和力矩的测量基于车辆感应到的加速度和角速度。这些测量结果与空气动力学模型和卡尔曼-施密特滤波器结合在一起以估计大气条件。将该新方法应用于火星科学实验室任务的数据,该任务于2012年8月将“好奇号”火星车降落在火星表面。将新估算算法的结果与基于机载压力的冲洗空气数据传感算法的结果进行了比较。车身前围的尺寸。比较表明,新提出的估算方法无需使用压力测量值即可提供与空气数据测量值一致的估算值。描述了对未来任务的影响,例如“火星2020”进入太空舱。

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