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A Particle Filter for Smartphone-Based Indoor Pedestrian Navigation

机译:基于智能手机的室内行人导航的粒子过滤器

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This paper considers the problem of indoor navigation by means of low-cost mobile devices. The required accuracy, the low reliability of low-cost sensor measurements and the typical unavailability of the GPS signal make indoor navigation a challenging problem. In this paper, a particle filtering approach is presented in order to obtain good navigation performance in an indoor environment: the proposed method is based on the integration of information provided by the inertial navigation system measurements, the radio signal strength of a standard wireless network and of the geometrical information of the building. In order to make the system as simple as possible from the user’s point of view, sensors are assumed to be uncalibrated at the beginning of the navigation, and an auto-calibration procedure of the magnetic sensor is performed to improve the system performance: the proposed calibration procedure is performed during regular user’s motion (no specific work is required). The navigation accuracy achievable with the proposed method and the results of the auto-calibration procedure are evaluated by means of a set of tests carried out in a university building.
机译:本文考虑了通过低成本移动设备进行室内导航的问题。所需的精度,低成本传感器测量的低可靠性以及GPS信号的典型不可用性使室内导航成为一个难题。本文提出了一种粒子滤波方法,以便在室内环境中获得良好的导航性能:该方法基于惯性导航系统测量结果,标准无线网络的无线电信号强度和建筑物的几何信息。为了使系统从用户的角度来看尽可能简单,假设在导航开始时未对传感器进行校准,并且执行了磁传感器的自动校准程序以改善系统性能:校准过程是在常规用户运动期间执行的(不需要进行特定的工作)。通过在大学建筑中进行的一组测试,可以评估所提出的方法可实现的导航精度以及自动校准过程的结果。

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