| Wireless location technology is widely used in public safety, road assistance and navigation, asset management and staff tracking. In recent years, with the popularity of intelligent terminals, such as mobile phones, and the wide coverage of WLAN, it is possible to locate the mobile terminals. As the building block makes the GPS-based and mobile station-based positioning methods cause large error when they are used in indoor environment, high-precision indoor positioning systems are more WLAN-based. At the same time, it is difficult to get proper signal propagation model in indoor environment, so the traditional positioning methods such as the triangulation will cause large error in indoor environment. Due to the database established prior the location phase, fingerprint-based positioning algorithm can eliminate the impact of the changing indoor environment and achive high accuracy.This paper mainly researchs on the RSS fingerprint-based positioning algorithms, and uses location clustering method in training phase to reduce the computation amount and to exclude the invalid location data. In positioning phase, this paper uses feedback filter to reduce the raw signal fluctuations from the changing circumstances. In addition, to achieve high accuracy in specific system, this paper optimizes the parameters of exsisting algorithms about getting nearest neighbors, determining the final location. To verify the effectiveness of this positioning method, an indoor positioning system based on ZigBee wireless protocal is built and some modifications are made in protocal to fit the locationing needs without effecting the normal ZigBee functions. Through the experiments, this location system achieves precision of over 50% within 2.5m and over 75% within 3m. |
