在外弹道测量数据处理中, 受计算机运算能力和内存限制, 普通计算机难以完成输入测速采样率为80 Hz/s的数据运算, 只能分段抽取10 Hz/s或者20 Hz/s数据进行运算, 无法提供50 Hz/s的弹道数据。但是数据分段抽点稀疏后, 一些特征点、动力特性及细节不能表现出来, 而高采样率80 Hz/s数据能够更多地获取飞行器运动特性。通过样条节点优化、算法改进, 采用不等距B样条节点, 基于集群高性能运算系统, 充分利用高频帧测速数据, 解算出高精度的弹道参数, 提高了特征点的弹道精度, 较好地满足了任务对高频帧率弹道的需求。

In data processing of the exterior ballistic measurement, it is difficult for the common computer to implement the data operation with input sampling rate of 80 Hz/s due to the limits of its operation capability and internal storage. It can only extract 10 Hz/s or 20 Hz/s data to calculate, and can not provide the ballistic data of 50Hz/s. However, when the data extraction is sparse, some feature points, dynamic characteristics and details will not be demonstrated, while the high sampling rate of 80 Hz/s data can obtain the motion characteristics of the aircraft. By means of spline node optimization, algorithm improvement and unequal-distance B-spline node, and by taking full advantage of high-frequency-frame speed measurement data, the cluster system based computing system can obtain the ballistic parameters with high precision, which can meet the requirements of high-frequency-frame rate trajectory.