Study On Indoor Localization Algorithm Based On WiFi And Bluetooth

With the rapid development of positioning technology,the application requirements of outdoor positioning and navigation systems can no longer meet the needs of people’s lives,so indoor positioning systems have become an important research object based on location information services.In indoor positioning,Wi Fi technology,Bluetooth technology,inertial sensor-based pedestrian track estimation positioning technology,ultra-wideband positioning technology,etc.are all key indoor positioning technologies.Wi Fi network has achieved large-area coverage,has long transmission distance,and simple networking,strong variability and other advantages.Bluetooth beacons are easy to deploy and have relatively low power consumption.Therefore,the use of Wi Fi technology and Bluetooth technology to be applied to indoor positioning systems is conducive to the promotion of indoor positioning technology and realizes research significance and application value.This thesis mainly focuses on the following researches on the indoor integrated positioning technology and implementation method based on Wi Fi and Bluetooth.First of all,when the Wi Fi positioning method fingerprint matching,when the indoor positioning area is large,the fingerprint data is too much,resulting in a large amount of positioning calculation,and a Wi Fi fingerprint WKNN positioning method based on K-means partition is proposed.This method uses the K-means algorithm to effectively divide the location area.According to the cluster center of each sub-region,it can quickly index the fingerprint point set with high similarity to the point to be measured.The WKNN positioning algorithm is used to calculate the location of the point to be measured.coordinate.The experimental results show that the positioning accuracy of the Wi Fi fingerprint WKNN positioning method based on K-means partition is better than that of the traditional WKNN positioning method.In order to simulate the actual environment,different standards of Gaussian noise are added to test the reliability of the positioning system.The Gaussian noise is 3d Bm When,the average positioning error is 1.79 m,the amount of positioning calculation is reduced by 42%,and the positioning accuracy is improved by 11%.It can be seen that the positioning method can reduce the positioning error caused by environmental factors,improve the real-time performance of the positioning system,and improve the positioning accuracy.Secondly,aiming at the problem of poor Bluetooth positioning signal stability,a Bluetooth beacon optimal positioning method based on multi-factor cost function is proposed.Using Bluetooth positioning technology as the co-location technology of Wi Fi positioning technology,the traditional method of using a single factor to select beacon nodes is improved,and the stability and stability of beacon nodes are comprehensively evaluated according to the mean value,variance,signal-to-noise ratio and signal visibility of the signal.reliability.The experimental results show that the positioning method after the optimized beacon is better than the positioning accuracy of the traditional optimization algorithm,and the optimized beacon plays a significant role in realizing high-precision indoor positioning.Finally,in view of the limited positioning accuracy of a single positioning technology,the advantages of Wi Fi positioning technology and Bluetooth positioning technology are fully utilized,and the Wi Fi and Bluetooth fusion positioning method based on Bayesian estimation is adopted.Use the Bluetooth beacon to optimize the positioning calculation.The Bluetooth positioning result is used as the coarse positioning area to meet the condition of high similarity with the position information of the Bluetooth coarse positioning result.The prior information distribution with high credibility is obtained by the Wi Fi position fingerprint matching calculation.Using Bayesian posterior distribution density function to estimate the coordinate deviation,which is used to correct the fusion positioning result.Simulation experiments show that the fusion positioning result is significantly improved compared to the positioning accuracy of the single positioning technology,with an average positioning accuracy of 1.58 m,and the positioning error caused by Gaussian noise is reduced.The fusion positioning is significantly better than the anti-noise performance of a single positioning.can effectively improve positioning accuracy.