An Improved Dynamic Prediction Fingerprint Localization Algorithm Based On KNN

摘要：

　　Because there are some problems in WiFi indoor positioning system such as low positioning accuracy and instability positioning results,the paper deeply studied KNN fingerprint localization algorithm and improved the algorithm according to the characteristics of signal propagation volatile in the indoor environment.The algorithm finds the nearest neighbor through dynamically predicting node position and filtering out the RP without similarity RSS vector at labels from wireless map in order to reduce time and computational complexity of the algorithm KNN.The experimental results show that the improved algorithm has been greatly improved in terms of location accuracy.

关键词： Indoor positioning KNN WiFi positioning Fingerprint positioning Android

作者: Lu Xuanmin Qiu Yang Yuan Wenle Yang Fan

作者单位: School of Electronics and Information Northwestern Polytechnical University 710072 Xian, China

会议类型: 国际会议

会议名称: 2016 Sixth International Conference on Instrumentation and Measurement,Computer,Communication and Control (IMCCC2016)(第六届仪器测量、计算机通信与控制国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 289-292

在线出版日期: 2016-07-21（万方平台首次上网日期，不代表论文的发表时间）