【摘要】 高速列车速度测量值的精确程度直接影响列控系统对列车运行的控制,根据列车速度等参数计算的列车制动距离的准确性也直接影响列车运行安全。针对既有测速算法的不足,提出了采用CKF-SVSF数据融合算法来提高列车速度测量的精确性。相对于传统的滤波算法,该算法充分结合了CKF和SVSF算法的优势。容积卡尔曼滤波算法(Cubature Kalman Filter,CKF)可更加精确地实现对非线性系统的状态估计;滑动可变结构滤波算法(Smooth Variable Structure Filter,SVSF)提供了在非线性系统的模型误差干扰下更具鲁棒性的测量方法。更多还原

【Abstract】 The speed measurement accuracy value will directly affect the degree how train control system control train.The accuracy of train braking length also affects the safety of train operation.This paper introduces the newly CKF-SVSF algorithm in contrast with traditional measurement methods’ disadvantages to improve the train speed measurement accuracy.Compare with the traditional filtering algorithm,the new algorithm combined CKF and SVSF algorithm’s advantage.Cubature Kalman Filter algorithm will improve the accuracy on the state estimation of nonlinear system.Also SVSF algorithm provide the robuster measurement method on estimation under the model uncertainties.更多还原