一种结合众包的WIFI指纹数据库自构建及更新算法

发布时间：2018-06-05 12:28

本文选题：指纹更新 + 动态聚类　；参考：《小型微型计算机系统》2017年11期

【摘要】：传统指纹法需要在离线阶段耗费大量的人力和时间成本去密集采集Wi-Fi数据,且位置指纹法的定位方式对环境变化很敏感,需要定期手动更新指纹数据库.近些年很多研究采用指纹数据库更新算法,但是这类算法默认是信任用户反馈的,不能准确过滤其中的错误数据.本文提出了一种结合众包的指纹数据库自构建及更新算法(AUAFC),在离线阶段只需在少量地标处采集指纹数据,在地标间使用手机传感器数据进行航位推算以提供基本的位置服务.为了减小地标识别的边界误差,AUAFC包含一种地标识别边界收敛算法.当服务器端接收到用户反馈时启动动态聚类算法提取可信数据更新指纹数据库或向数据库中植入新的地标.实验结果表明,地标识别边界收敛算法能使地标点的定位误差缩小至2.6米左右,而且相比较于传统指纹更新算法,本文算法AUAFC能准确的提取有效反馈信息并准确的植入新地标及更新原有的指纹数据库.
[Abstract]:The traditional fingerprint method needs a lot of manpower and time cost to collect Wi-Fi data in the off-line phase, and the location method of the location fingerprint method is sensitive to environmental changes, so it is necessary to update the fingerprint database manually periodically. In recent years, many researches have adopted fingerprint database updating algorithm, but these algorithms trust user feedback by default and can not filter the error data accurately. In this paper, a fingerprint database self-constructing and updating algorithm combined with crowdsourcing is proposed. Only a small number of landmarks need to be collected at off-line stage, and mobile phone sensor data are used to calculate the landmarks in order to provide basic location services. In order to reduce the boundary error of Landmark recognition, AUAFC includes a boundary convergence algorithm for Landmark recognition. When the server receives user feedback, it starts the dynamic clustering algorithm to extract trusted data to update the fingerprint database or insert new landmarks into the database. The experimental results show that the boundary convergence algorithm of Landmark recognition can reduce the location error to about 2.6 meters, and compared with the traditional fingerprint updating algorithm, The algorithm AUAFC can accurately extract effective feedback information, accurately implant new landmarks and update the original fingerprint database.
【作者单位】：江南大学物联网工程学院物联网技术应用教育部工程研究中心;
【基金】：国家自然科学基金项目(61170121)资助江苏省青年科学基金项目(BK20150159)资助
【分类号】：TN92

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