Aiming at the problem of gliding near space hypersonic vehicle (NSHV) trajectory prediction, a trajectory prediction method based on aerodynamic acceleration empirical mode decomposition (EMD) is proposed. The method analyzes the motion characteristics of the skipping gliding NSHV and verifies that the aerodynamic acceleration of the target has a relatively stable rule. On this basis, EMD is used to extract the trend of aerodynamic acceleration into multiple sub-items, and aggregate sub-items with similar attributes. Then, a prior basis function is set according to the aerodynamic acceleration stability rule, and the aggregated data are fitted by the basis function to predict its future state. After that, the prediction data of the aerodynamic acceleration are used to drive the system to predict the target trajectory. Finally, experiments verify the effectiveness of the method. In addition, the distribution of prediction errors in space is discussed, and the reasons are analyzed.

中文翻译：

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基于气动加速EMD分解的NSHV弹道预测算法

针对近空高超音速飞行器（NSHV）滑行轨迹预测问题，提出了一种基于气动加速经验模态分解（EMD）的轨迹预测方法。该方法分析了跳跃式滑行NSHV的运动特性，并验证了目标的空气动力学加速度具有相对稳定的规律。在此基础上，使用EMD将空气动力学加速度的趋势提取到多个子项中，并汇总具有相似属性的子项。然后，根据空气动力学加速度稳定性规则设置先验基础函数，并且通过基础函数拟合汇总数据以预测其未来状态。之后，使用空气动力学加速度的预测数据来驱动系统以预测目标轨迹。最后，实验证明了该方法的有效性。此外，讨论了空间中预测误差的分布，并分析了原因。