The invention belongs to the technical field of train running speed estimation, and discloses a multi-model train running speed estimation method based on high-order Kalman filtering, which comprises the following steps: S1, establishing a train multi-modal running model and a train running speed measurement model in combination with an actual train running environment; s11, establishing a train multi-modal operation model; s12, establishing a train running speed measurement model; s2, estimating the running state of the train based on high-order Kalman filtering; s21, high-order representation of the train operation state model; s22, identifying the error statistical characteristics of the high-order state model; s23, estimating high-order feature information; and S24, estimating the running speed of the high-speed train based on high-order Kalman filtering. According to the multi-model train running speed estimation method based on high-order Kalman filtering, the performance of the filter and the estimation precision of high-order information are improved.
本发明属于列车运行速度估计技术领域,公开了一种基于高阶卡尔曼滤波的多模型列车运行速度估计方法,包括以下步骤:S1、结合实际列车运行环境,建立列车多模态运行模型及列车运行速度测量模型;S11、建立列车多模态运行模型;S12、建立列车运行速度测量模型;S2、基于高阶Kalman滤波,对列车运行状态进行估计;S21、列车运行状态模型的高阶表示;S22、高阶状态模型误差统计特性辨识;S23、高阶特征信息估计;S24、基于高阶Kalman滤波的高速列车运行速度估计。本发明采用上述的一种基于高阶卡尔曼滤波的多模型列车运行速度估计方法,提高了滤波器的性能以及对高阶信息的估计精度。
Multi-model train operation speed estimation method based on high-order Kalman filtering
一种基于高阶卡尔曼滤波的多模型列车运行速度估计方法
2024-11-01
Patent
Electronic Resource
Chinese
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