Research Of Intelligent Indoor Guide And Positioning System Based On Zigbee

Along with the rapid development of wireless sensor networks, the transmission and access of information have ushered in a new era. Mobile terminals provide personalized services at anywhere7/24. It will become a research hotspot. GPS positioning system cannot be used in indoor. To make up the blank in indoor electronic guide, this research designed indoor electronic guide system based on Zigbee wireless sensor networks. This guide system can provide personalized guide services based on the position of each terminal which acquired by signal acquisition.This paper begins with an overview of the indoor wireless location technology research background. Wireless signal propagation models, the relationship between wireless model parameters A and N and the environment, and the impact on the received signal strength RSSI (Received Signal Strength Indicator) has been studied. Indoor environment is relatively complex, multi-existence of non-line of sight is exists. In order to reduce the NLOS error and problems in locating model, we propose a new method for positioning use real-time dynamic parameters. First, based on artificial neural network algorithm, we made RSSI measurements close to (LOS) measurement. Then in the region through the selected reference node communication between real-time dynamically estimate the environmental parameter values. Experiments show that the algorithm not only reduces the non-line-of-sight error in RSSI ranging technology, and can be dynamically adjusted according to actual conditions real-time positioning model parameters, effectively improves the positioning accuracy. This paper is verified by school interior space seat experimental environment application scenario for positioning performance measurement. Experimental results show that the algorithm reduces the error, improve the accuracy compared with the traditional positioning algorithm.Build Zigbee wireless network positioning platform, design the improved positioning algorithm. Its hardware adopts TI CC2430as the core chip of wireless sensor network node. Acquire and process information about indoor environment. Software architecture is based on Android platform and the Linux kernel.