Research On Indoor Localization Technology Based On AP Location Discrimination Ability

With the rise of mobile Internet,people's application and demand for location-based privacy services are increasing.Due to the widespread application of WLAN(Wireless Local Area Network),the indoor location technology based on WIFI fingerprint can be directly used for target location without additional equipment,and the location accuracy is high and the compatibility is strong.The indoor location technology based on WIFI location fingerprint is to match the fingerprint in the fingerprint database by receiving the received signal strength indication(RSSI)at the access point(AP)to determine the target location.However,when the indoor environment changes dynamically,the AP communication is interfered by the environment,and the positioning result will have a large error.Aiming at the problem that the existing fingerprint location algorithm can 't reduce the abnormal RSSI interference in the indoor complex dynamic environment,and the traditional particle filter algorithm can't guarantee the reliability of the observation value.This paper uses the WIFI fingerprint identification method,particle filter algorithm and pedestrian dead reckoning(PDR)technology to realize the static location and tracking location of the target.Experimental results show that the algorithm proposed in this paper can still maintain high positioning accuracy and stability in complex dynamic positioning environment.The main research work of this paper includes:In order to solve the problem that the indoor dynamic environment interferes with the AP communication in different areas,this paper proposes an indoor security location algorithm based on the AP location discrimination ability(SLABLDA).In the off-line phase,the method saves all the initial fingerprints to the fingerprint database after preprocessing,and retains the integrity of the AP signal.In the off-line detection stage,the AP location discrimination function is proposed to effectively eliminate the abnormal RSSI caused by the regional dynamic environment,and accurately calculate the AP location discrimination ability of different regions.In the online stage,the similarity between the reference node and the target node is calculated by RSSI minimum difference matched model,and the AP location discrimination ability is included in the position estimation,whi ch greatly improves the online positioning accuracy.Aiming at the problems of traditional particle filter,such as the tracking effect is greatly disturbed by environmental factors,particle dilution after repeated resampling,this paper proposes a tracking and localization algorithm of trusted particle filter based on pedestrian dead reckoning(Pedestrian Dead Reckoning,PDR).In the off-line phase,the PDR motion model and state equation are established,and the target is estimated and judged by on-line tracking,thus the credibility of the observed value is detected.In the importance sampling stage,the method classifies the particles by setting the particle weight threshold,and then samples the particles randomly and optimally,which solves the problem of particle sample dilution.Through the experimental analysis,the algorithm can accurately track the target and realize the location in the presence of environmental interference factors.