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A smartphone localization algorithm using RSSI and inertial sensor measurement fusion

机译:一种使用RssI和惯性传感器测量融合的智能手机定位算法

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摘要

Indoor navigation using the existing wireless infrastructure and mobile devices is a very active research area. The major challenge is to leverage the extensive smartphone sensor suite to achieve location tracking with high accuracy. In this paper, we develop a navigation algorithm which fuses the WiFi received signal strength indicator (RSSI) and smartphone inertial sensor measurements. A sequential Monte Carlo filter is developed for inertial sensor based tracking, and a radiolocation algorithm is developed to infer mobile location based on RSSI measurements. The simulation results show that the proposed algorithm significantly outperforms the extended Kalman filter (EKF), and achieves competitive location accuracy compared with the round trip time (RTT) based ultra-wideband (UWB) system.
机译:使用现有的无线基础设施和移动设备进行室内导航是一个非常活跃的研究领域。主要的挑战是利用广泛的智能手机传感器套件来实现高精度的位置跟踪。在本文中,我们开发了一种导航算法,该算法将WiFi接收信号强度指示器(RSSI)与智能手机惯性传感器测量结果融合在一起。针对基于惯性传感器的跟踪,开发了顺序蒙特卡洛滤波器,并开发了无线电定位算法,以基于RSSI测量来推断移动位置。仿真结果表明,与基于往返时间(RTT)的超宽带(UWB)系统相比,该算法明显优于扩展卡尔曼滤波器(EKF),并具有竞争优势的定位精度。

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