Research And Design Of WIFI Indoor Positioning Algorithm Based On Location Fingerprint

With the rapid development and application of the Internet of Things(IoT),indoor positioning technology based on location needs has become a research hotspot for scholars at home and abroad.In recent years,among many indoor positioning methods,positioning methods based on wireless local area network(WLAN)have become a research hotspot due to the wide coverage of wireless infrastructure and the rapid update of WIFI technology.Although there are several challenges in the WLAN-based positioning method,it is still the most researched method that would be popularized and applied in the future because of its conventional,practical,and low-cost characteristics.This thesis systematically analyzes and studies the two-stage process of indoor location technology based on WLAN location fingerprint method.The main research work and contributions include: It focuses on the offline stage process of indoor location technology based on WLAN location fingerprint method.Several signal propagation loss models are analyzed.Based on the free space path loss model,an improved algorithm for automatically constructing radio maps based on ray tracing(AMRC-RT)is proposed,aiming to Automated construction.Finally,the measured value is compared with the automatically constructed prediction value,and an RSS adaptive algorithm is proposed to reduce the interference effect of "human presence effect";the online phase process of indoor location technology based on WLAN location fingerprint method is focused.It analyzes the influence of each parameter on the WKNN algorithm.Then,aiming at the problems of the WKNN online matching algorithm,an AMRC-RT-based WKNN combined post-processing of Kalman filter algorithm is proposed.The final algorithm and simulation prove that the proposed algorithm solves the problems of positioning point drift and positioning trajectory discontinuity in the traditional WKNN algorithm,and effectively improves positioning accuracy.