室内定位方法及研究

Research on Indoor Positioning Methods

随着经济发展,基于位置的服务已成为人们生活中一种重要的信息服务。图书馆作为一个可提供图书借阅的单位,虽有电子化借阅系统,但因其室内环境复杂,读者因缺少位置服务难以快速确定自身及图书位置。针对读者寻书过程中场景变换较多、书架分布可视化程度低导致寻找不便与已有寻书方法人员定位精度低等问题,本文基于iBeacon设备,研究位置指纹定位中特征值提取与异常点检测两大关键技术,通过引入高斯核密度估计检测初始异常值,选取卡尔曼滤波提取特征值,然后利用WKNN算法进行定位。实验表明,该算法在保证定位效率的同时可提高定位精度。最后基于Android手机,设计了图书馆定位查询系统,通过结合空间查询技术与iBeacon指纹定位技术,为消费者提供更佳的位置信息服务。

With the development of economy,services based on location have gradually become a significant part of people’s daily life.As an institution supplying book lending service,even most libraries have been equipped with electronic lending system,readers always find it difficult to confirm the position of themselves and the books due to the lack of location services and the complexity of indoor environment.This article raised a method to study two key technologies,feature extraction and outlier detection in fingerprint location to deal with the inconvenience of finding precise position of targeted books,which solves the problems of too many scene changes and the low visualization of bookshelves.Bases on iBeacon device,this article uses the WKNN algorithm to locate by introducing Gaussian kernel density estimation to detect the initial anomaly and selecting Kalman filter to extract eigenvalue.The result shows that this type of algorithm can improve the accuracy of locating with no loss of calculating efficiency.Based on Android operating environment,we designed a query system of library location,which could supply readers with better location services by the combination of the spatial query technology and iBeacon fingerprint location technology.