Research On Indoor Localization Algorithm Based On Artificial Neural Network And ZigBee Technology

With the rapid development of sensor technology and wireless data communication technology,wireless sensor network technology(WSN)has entered a new stage of development.As a part of the Internet of Things system,wireless sensor network in large buildings such as warehouses,mines,shopping malls and other indoor environment has a large number of applications.In these applications to accurately determine the indoor location of the event is important,which may improve the overall performance of the wireless sensor network.So the localization algorithm based on wireless sensor network is more and more concerned by researchers at home and abroad.Because ZigBee technology has the characteristics such as low power consumption,high expandability,so the hardware platform of this algorithm is based on ZigBee technology.In this paper,use the CC2530 chip from Texas Instruments and Zigbee technology to build a ZigBee wireless sensor network hardware platform,relying on the hardware platform learn some traditional localization algorithms,and mainly studies the localization algorithm based on the signal loss model.Aiming at the influence of wireless signals' s inaccurate and unstable,use the linear non-linear fitting ability of ANN model to optimize the localization algorithm.Firstly,an artificial neural network is used to fit the mapping model between RSSI and distance.Use the artificial neural networks can make the positioning algorithm when RSSI value convert to distance information no longer limited by select the fixed environment parameters path loss model problem.RSSI measurements values with noise can be used directly with the actual coordinate position to train the network.The RSSI value of the wireless sensor collected by the ZigBee wireless sensor network hardware platform is used as the input layer of the trained neural network model.The distance information required for the localization calculation is obtained at the output layer of the neural network.Finally,use the weighted centroid localization to calculate the coordinates of the nodes to be measured.The experimental results show that the indoor location algorithm based on the artificial neural network and ZigBee technology can provide better location results compared with the path loss model,so as to improve the accuracy of the indoor positioning results.