To address the issues of poor accuracy and stability in Bluetooth/WiFi hybrid positio-ning,a hybrid positioning method using Bluetooth and WiFi based on location information finger-print is proposed,which includes an offline phase and an online phase.In the offline phase,Blue-tooth and WiFi signal strength data are collected and segmented into two groups.The first group is used to construct Bluetooth,WiFi,and Bluetooth/WiFi hybrid fingerprint databases,while the second group is used to train fingerprints,which are subsequently matched with the Bluetooth,WiFi,and hybrid fingerprint databases to estimate positions for Bluetooth,WiFi,and Bluetooth/WiFi.A location information fingerprint database is then constructed based on these estimated po-sitions and reference points.In the online phase,Bluetooth,WiFi,and Bluetooth/WiFi hybrid fingerprint positioning is performed.The estimated positions of Bluetooth,WiFi,and hybrid fin-gerprints are combined to generate online location information fingerprints,which are then matched with the location information fingerprint database using the K-nearest neighbors(KNN)algorithm.Experimental results show that the proposed method significantly outperforms weighted K-nearest neighbors(WKNN),Gaussian process regression(GPR),and support vector machine(SVM)methods in terms of positioning accuracy on two public datasets.In Dataset 1,the root mean square error(RMSE)of the proposed method decreased by at least 41.21％,48.33％,and 67.56％compared to WKNN,GPR,and SVM,respectively.In Dataset 2,the mean absolute error(MAE)of the proposed method was 0.914 meters,significantly outperforming WKNN,GPR,and SVM.
BluetoothWiFiHybrid fingerprintLocation information fingerprintBluetooth/WiFi hybrid positioning
维普
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