Research On WiFi Indoor Location Method Based On Location Fingerprint

Nowadays,people's demand for indoor positioning is increasing.Due to the wide use of WiFi devices,the technology of indoor positioning using WiFi has been widely concerned.At present,in the field of WiFi location,some researchers mainly use WiFi fingerprint location method to measure the target location node more accurately according to the unique RSSI signal strength characteristics of the location area.Because the WiFi fingerprint location algorithm based on WKNN and the WiFi fingerprint location algorithm using Kmeans+RVM have some problems,such as the positioning accuracy is not up to standard,the collected signal is unstable and so on,this paper proposes an improved algorithm.In the off-line stage,the kernel Kmeans clustering algorithm is used to divide the collected signal according to the strong and weak clustering,and the collected signal eigenvalues are saved in the fingerprint database In the online phase,based on the traditional WKNN algorithm,the distance between the selected K nearest neighbors and the center node of the nearest neighbors and the node to be tested is analyzed,and the distance between the fingerprint node and the node to be tested and the distance between the K nearest neighbors and the node to be tested in the fingerprint database are calculated The distance of the center node is mixed weighted to get the weight and the positioning coordinates.Through MATLAB simulation,the results show that the algorithm can effectively solve the original defects and improve the positioning error and stability.Therefore,the improved WiFi fingerprint location algorithm proposed in this paper is more accurate and has good practical value.