An Indoor Positioning Method Based on RSSI Probability Distribution

摘要：

　　In view of the influence of the time-variation of RSSI on the positioning accuracy in Wi-Fi indoor positioning,this paper proposes to use the probability distribution of RSSI value as a fingerprint feature over a period of time,and combines the dimension reduction algorithm and the weighted K nearest neighbor algorithm to achieve positioning.The method firstly calculates the probability distribution of the received RSSI value,uses the dimensionality reduction algorithm to reduce the dimension of the statistical probability distribution.The K-reference points with the smallest Euclidean distance were combined with the weighted nearest neighbor algorithm to obtain the positioning results.Through simulation experiments,it is shown that the positioning accuracy is higher than the traditional method,and the positioning time is significantly reduced.

作者: Shipeng Li Xinyu Yang Rui Zhao Yuqing Liu Xue Zhou Libiao Zhang

作者单位: School of Information Science and Technology,Northeast Normal University,Changchun,China

会议类型: 国际会议

会议名称: The 2nd International Symposium on Application of Materials Science and Energy Materials (SAMSE 2018) 第二届材料科学应用与能源材料国际研讨会2018年

会议地点: 上海

会议语种:英文

页码: 1-6

在线出版日期: 2018-12-17（万方平台首次上网日期，不代表论文的发表时间）