Indoor Positioning Technology Research Based On WLAN

With the increasing development of wireless communication technology and high-precision positioning service people demands, indoor position is becoming a hotspot based on location information services (Location Based Services, LBS). Although the global satellite positioning system --GPS system technology has been very mature, but the GPS system positions by transmitting microwave signals, and the microwave signals can not penetrate walls into the interior, so that makes the indoor high-precision positioning becoming a top urgent problem.Fingerprinting positioning method based-on WLAN is introduced in this paper. Firstly, establish an offline fingerprint database by collecting the fingerprint data within the targeted area for future positioning. Then, using a mobile terminal in position stage to collect measurement data. Finally, we can get positioning result by matching the measurement data and the data in offline fingerprint database. The process of establishing an offline fingerprint database is called offline stage. The process of achieving position is called online stage, online stage can be divided into signal extraction stage and positioning stage. This paper studies signal extraction stage and positioning stage.This paper introduce and achieve the Kalman filter to extract the signal in signal extraction stage. In process of signal propagation, RSSI value tend to be interferenced by the movement of persons, co-channel interference and so on,then the value of RSSI will decline. While the RSSI value as the most important location information, which can lead to inaccurate measurements positioning accuracy. There is a variety of factors susceptible to interference the RSSI value of WLAN signal. The Kalman filter algorithm will be added to the positioning process, so the positioning process can effectively eliminate random signal noise, then the measurement value is closer to the true value. The optimum parameter values of Kalman filter algorithm is determined by simulating.This paper introduce and achieve KNN algorithm to position in positioning stage. Positioning stage is the process of matching the measurement data from mobile terminal and the data in offline fingerprint database. The data in offline fingerprint database carries real location information, the positioning result is a data in offline fingerprint database which is closet to the data from mobile terminal. This paper use KNN algorithm as positioning algorithm and determine the optimum parameters by simulating.Based on theory, an indoor location app based on Android platform is designed in this paper. Using the JAVA programming language to achieve indoor positioning function which add the Kalman filter. By testing in physical environment, we analyze and compare the positioning result, the result shows physical experiment close to the theoretical simulation, proving the fingerprint location can be realized in engineering. The system which add the Kalman filter algorithm can effectible eliminate random signal noise, and has good performance and high positioning accuracy.The WLAN indoor positioning system has better positioning performance. Due to the distribution of WLAN showed generalized and widespread trend, and WLAN-based indoor positioning is easy to realize and has a low cost, the system has high application value.