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Interacting multiple model for improving the precision of vehicle-mounted global position system

机译:交互多种模型以提高车载全球定位系统的精度

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To improve the precision of low-cost, Vehicle-mounted global position system (GPS), this paper presents the multi-source information fusion algorithm of vehicle navigation, which is based on the interacting multiple model (IMM). Considering vehicle kinematics and dynamic characteristics, as well as its braking capacity in extreme accelerating situations, this study establishes the clothoid model, which shows longitudinal and lateral constant speed motion, and the Adaptive Current Statistics (ACS) model, which shows the acceleration of a vehicle. Through the parametric estimation of interactivity, filtering, and updating of probability, the vehicle trajectory is predicted within a period of time, and high-precision dead-reckoning is therefore achieved. Comparative analysis shows that the above algorithm can improve the precision of vehicle-mounted GPS/inertial navigation system. (C) 2015 Elsevier Ltd. All rights reserved.
机译:为了提高低成本车载全球定位系统(GPS)的精度,提出了一种基于交互多模型(IMM)的车辆导航多源信息融合算法。考虑到车辆的运动学和动态特性,以及在极端加速情况下的制动能力,本研究建立了回旋模型和自适应电流统计模型,该回旋模型显示了纵向和横向匀速运动,而自适应电流统计模型则显示了加速度。车辆。通过交互性的参数估计,过滤和概率更新,可以在一段时间内预测车辆的轨迹,从而实现高精度的死机跟踪。对比分析表明,以上算法可以提高车载GPS /惯性导航系统的精度。 (C)2015 Elsevier Ltd.保留所有权利。

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