一种基于粒子滤波的智能移动终端室内行人定位算法
发布时间：2018-07-25 16:18
【摘要】：针对现有室内定位算法精度较低、部署维护成本高、鲁棒性不足等缺点,提出一种基于粒子滤波的室内无线定位自学习算法,将在室内环境下行人定位问题描述为动态系统状态估计问题,将智能移动终端与室内定位相结合,分别利用智能移动终端内置的传感器和Wi-Fi模块感知用户运动和用户所在环境,并利用粒子滤波对得到的定位数据进行滤波融合.同时将定位结果实时上传至服务器,递增式地构建位置指纹库,并根据时间标签不断地更新指纹库,以适应室内环境的动态变化.实验结果表明,该定位算法有效克服了现有室内定位的局限性,提高了定位精度及鲁棒性.
[Abstract]:Aiming at the shortcomings of the existing indoor positioning algorithms, such as low precision, high cost of deployment and maintenance, and insufficient robustness, a self-learning algorithm for indoor wireless location based on particle filter is proposed. The problem of pedestrian location in indoor environment is described as a dynamic system state estimation problem. The intelligent mobile terminal is combined with indoor positioning, and the sensor and Wi-Fi module built into the intelligent mobile terminal are used to perceive the user's motion and the user's environment, respectively. And the particle filter is used to filter and fuse the location data. At the same time, the location result is uploaded to the server in real time, the location fingerprint database is constructed incrementally, and the fingerprint database is updated continuously according to the time label to adapt to the dynamic change of indoor environment. The experimental results show that the algorithm overcomes the limitations of indoor positioning and improves the accuracy and robustness of the localization.
【作者单位】： 燕山大学信息科学与工程学院;河北省计算机虚拟技术与系统集成重点实验室;
【基金】：河北省自然科学基金项目(F2012203170)资助;河北省自然科学基金项目(F2012203188)资助
【分类号】：TN929.5;TP301.6
本文编号：2144368
[Abstract]:Aiming at the shortcomings of the existing indoor positioning algorithms, such as low precision, high cost of deployment and maintenance, and insufficient robustness, a self-learning algorithm for indoor wireless location based on particle filter is proposed. The problem of pedestrian location in indoor environment is described as a dynamic system state estimation problem. The intelligent mobile terminal is combined with indoor positioning, and the sensor and Wi-Fi module built into the intelligent mobile terminal are used to perceive the user's motion and the user's environment, respectively. And the particle filter is used to filter and fuse the location data. At the same time, the location result is uploaded to the server in real time, the location fingerprint database is constructed incrementally, and the fingerprint database is updated continuously according to the time label to adapt to the dynamic change of indoor environment. The experimental results show that the algorithm overcomes the limitations of indoor positioning and improves the accuracy and robustness of the localization.
【作者单位】： 燕山大学信息科学与工程学院;河北省计算机虚拟技术与系统集成重点实验室;
【基金】：河北省自然科学基金项目(F2012203170)资助;河北省自然科学基金项目(F2012203188)资助
【分类号】：TN929.5;TP301.6
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