[01] Shi Chen, School of Computer Science and Technology, Nanjing University of Technology, Nanjing, China; School of Information Engineering, Yancheng Teachers University, Yancheng, China.

With the rapid development of the information age, people are no longer satisfied with outdoor location-based services, and indoor localization has become a hot topic of discussion. Related technical personnel have also actively explored indoor positioning technology. At present, many indoor localization scenes are no longer a single single-layer environment, and position estimation is also required in a multi-layer environment. However, the existing work shows certain limitations to the problem of floor localization accuracy and computational complexity. This paper proposes a localization system capable of floor recognition. The system is divided into offline phase and online phase. In the offline phase, we deploy the Bluetooth APs to collect RSS signal strength values at the planned collection points and establish a local fingerprint database. Then use linear discriminant analysis to establish a floor recognition model. In the online stage, the floor location is determined first, and then the specific location of the target is obtained through the improved KNN algorithm. We collected real experimental data on two floors. Experimental results show that we can quickly and accurately locate a floor through a small amount of AP fingerprint information, reduce the complexity of localization calculations, and accurately locate the target's specific location on the floor.

Indoor Localization, Multi-floor Recognition, Wireless Network, Floor Classification

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