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空间运载火箭飞行计划的一个重要组成部分是对诸如驻留轨道入轨和有效载荷分离各种事件中的性能误差进行分析。性能误差可在这些事件中产生位置误差、速度误差及时间误差。性能误差的方差和协方差通常由7×7阶的空间一时间误差协方差矩阵决定。在预定的飞行时间里,位置误差和速度误差可认为是随预定时间而变的条件误差,因而需要计算6×6阶条件空间协方差矩阵。通常用数值方法来计算条件矩阵。本文提出了一种把7×7阶或更高阶的空间一时间协方差矩阵转换为商用大力神运载火箭用的6×6阶空间协方差矩阵的综合研究方法。这种方法是以条件多变量的正态分布统计理论为依据的。利用方差相等性假设实验得到的 x~2,理论矩阵可与数值计算得到的矩阵相比较。假设买验结果说明,6×6阶条件空间协方差矩阵的理论值与数值计算值之间没有明显的区别。
An important part of the space launch rocket flight plan is the analysis of performance errors in various incidents such as orbital orbit separation and payload separation. Performance error can produce position error, speed error and time error in these events. The variance and covariance of the performance error are usually determined by a space-time error covariance matrix of 7 × 7 orders. For a given time of flight, the position error and the speed error can be considered as conditional errors that change with a predetermined time, so a 6 × 6-order conditional space covariance matrix needs to be calculated. The numerical method is usually used to calculate the condition matrix. In this paper, we present an integrated method for transforming a covariance matrix of 7 × 7 order or higher into a 6 × 6 order covariance matrix for a commercial launch vehicle. This method is based on the conditional multivariate normal distribution statistical theory. Using the x ~ 2 experimental hypothesis of equality of variance, the theoretical matrix can be compared with the numerical matrix. Assuming the test results show that there is no significant difference between the theoretical and numerical values of the 6 × 6-order conditional space covariance matrix.