Research And Implementation Of WLAN Indoor Location Based On Location Fingerprint

With the development of WLAN,high-accuracy indoor positioning technology has gradually become the key to indoor location service.As the application of WLAN is more and more common,and the demand for indoor location-based services is getting more and more urgent,the WLAN-based location system becomes a research hotspot.This paper mainly studies the indoor location technology of WLAN based on location fingerprinting,and improves the accuracy and real-time of the indoor location system by improving the original location method.The research on WLAN indoor location based on location fingerprinting is mainly divided into two parts: the fingerprint database establishment stage and the online positioning stage.At the stage of establishing the fingerprint database,a fingerprint database of the signal coverage is obtained by establishing an experimental environment and actually measuring RSSI signal intensity,and a related model is established.Online positioning phase,the need for positioning of the client signal real-time sampling and tracking,application-specific methods to search in the fingerprint database matching location.Based on the original matching algorithm,an improved localization algorithm based on region partitioning is proposed.Filtering processing is added to the indoor positioning system to linearize the obtained positioning results again,so that the positioning accuracy of the positioning system is further improved.The method improves the relevant problems encountered in the actual positioning process,and optimizes the fingerprint database establishment phase and the online matching phase separately to continuously improve the positioning accuracy of the indoor positioning system.Through the comparison and analysis of the positioning performance of the improved indoor location and the improved front location fingerprint,it is found that the improved indoor location system has greatly improved the positioning accuracy and greatly improved in stability and real-time performance.