高超声速飞行器分解集成轨迹预测算法

针对无动力滑翔高超声速飞行器的轨迹预测问题,提出了分解集成轨迹预测模型。依据运动轨迹的周期跳跃特性,运用先集成再分解的轨迹预测思路,首先将运动轨迹序列分解为具有趋势性、周期性和随机性特征的子序列,再针对每项子序列的特征采用相应的子轨迹预测模型,最后将各子轨迹预测模型预测结果的集成作为最终预测值。由于子序列与子轨迹预测模型具有更高的契合度,使得分解集成轨迹预测 算法相对于使用单一模型的轨迹预测算法更具优势。仿真实验表明,分解集成轨迹预测算法显著提高了轨迹预测精度。

Decomposition ensemble trajectory prediction algorithm for hypersonic vehicle

Aiming at the trajectory prediction of unpowered gliding hypersonic vehicle and its application requirements, a decomposition ensemble trajectory prediction model is proposed.Firstly, according to the periodicity leap characteristic of the hypersonic vehicle, the trajectory sequence is decomposed into sub-sequences with trend, periodicity and randomcharacteristics by using the thought of decomposition and integration. Then, using the corresponding trajectory prediction model to predict each trajectory sub-sequence on thebasis of sub-sequence characteristics. Finally, the ensemble of the prediction result of each trajectory prediction sub-model is taken as the final prediction value.Due to the high degree of fit between the sub-sequence and the trajectory prediction sub-model, the decomposition ensemble trajectory prediction algorithm has moreadvantages than the trajectory prediction algorithm using a single model. The simulation results show that the decomposition ensemble trajectory prediction algorithm canimprove the accuracy of trajectory prediction effectively.