多维空间中基于模式的移动对象轨迹预测

本文在分析了现有轨迹模型基础上，提出了轨迹相似度计算模型以及基于移动对象加速度和轨迹偏转角的移动对象轨迹预测模型，综合计算和预测模型提出了移动对象轨迹预测方法. 该方法包括：1）对历史轨迹基于轨迹相似度进行聚类分析，形成训练集聚类，并基于各训练集聚类对目标移动对象的轨迹数据进行轨迹相似度并行计算，找出最大相似度的历史轨迹；2）结合历史轨迹以及移动对象加速度和轨迹偏转角的预测模型进行轨迹预测. 经过对测试轨迹集进行实验的结果表明，本方法在误差为500 m以内的预测准确率能达到90%以上，而且预测时间相对较短，具有较高的实用价值.

Pattern-Based Moving Target Trajectory Prediction in Hyperspace

Based on the analysis of the existing trajectory model, this paper proposes a trajectory similarity calculation model and a moving object trajectory prediction model based on moving object acceleration and trajectory deflection angle. The moving object trajectory prediction method is proposed by comprehensive calculation and prediction model. The method comprises the following steps. 1) The historical trajectory is clustered based on the similarity of the trajectory to form the training cluster, and the trajectory similarity of the trajectory data of the target moving object is calculated based on each training cluster to find the maximum similarity historical trajectory. 2) The trajectory prediction is made based on the historical trajectory and the prediction model of moving object acceleration and trajectory deflection angle. The experimental results show that the prediction accuracy of the method is more than 90% in 500 m range, and the prediction time is relatively short, which has high practical value.