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Method for estimating position of vehicle using Interacting Multiple Model filter

机译:交互多模型滤波器在车辆位置估计中的应用

摘要

vehicle position estimation method using an interactive multi-model filter according to the present invention, the kinematic model predicted value calculated by the kinematic model EKF and the dynamic model predicted value and calculating a dynamic model, extended Kalman filter, calculating a value of the kinematic model of the filter between the measurement value indicating the current position of the kinematic model predicted value and vehicle and the vehicle dynamics model predicted value and the value of the dynamic model between the filtered value of the measured value that indicates the current position and calculating, by integrating the dynamic model filtering value and the kinematic model filter value for calculating the final correction value and a step. With a vehicle position estimation method using an interactive multi-model filter according to the present invention, in the GPS reception is poor location can estimate the position of the vehicle stably, even if the operation is an error in the extended Kalman filter error value a can be reduced, and the advantage of being able to more accurately estimate the position of the vehicle by setting the weight to be added to the data than reasonably calculated from the kinematic model extended dynamic model calculated data from the Kalman filter and the Extended Kalman filter. ;
机译:根据本发明的使用交互式多模型滤波器的车辆位置估计方法,由运动学模型EKF计算出的运动学模型预测值和动态模型预测值并计算动态模型,扩展卡尔曼滤波器,计算运动学值表示运动模型预测值和车辆的当前位置的测量值与车辆动力学模型预测值之间的滤波器的模型,以及表示当前位置的测量值的滤波值之间的动力学模型的值,并进行计算,通过将动态模型滤波值和运动模型滤波值进行积分来计算最终校正值和一个步骤。使用根据本发明的使用交互式多模型滤波器的车辆位置估计方法,在GPS接收不良的情况下,即使操作是扩展的卡尔曼滤波器误差值a中的误差,也可以稳定地估计车辆的位置。与通过运动模型,动态模型,卡尔曼滤波器和扩展卡尔曼滤波器计算的数据合理计算相比,通过设置要添加到数据中的权重,可以更加准确地估计车辆的位置。 ;

著录项

  • 公开/公告号KR101177374B1

    专利类型

  • 公开/公告日2012-08-29

    原文格式PDF

  • 申请/专利权人

    申请/专利号KR20100072207

  • 发明设计人 선우명호;주건엽;조기춘;

    申请日2010-07-27

  • 分类号G01S19/45;

  • 国家 KR

  • 入库时间 2022-08-21 17:07:35

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