| With the advent of the information age and the rapid development of computer technology,wireless technology is also constantly innovating.In the complex indoor environment,there are non-visual range,multi-diameter and other variable factors interference,so GPS,cellular mobile and other location positioning accuracy is very low or even cannot be used.This makes accurate positioning of indoor environments or small Spaces with poor vision extremely important.Due to the increasing demand for indoor positioning in society,it also promotes the development and close attention of its related technologies.This paper mainly introduces the indoor positioning technology background and the status quo of research at home and abroad,then introduces the related concepts of ZigBee wireless technology,and through comparing the positioning algorithm to select the RSSI localization algorithm,however,the classic based on signal quality in indoor localization algorithm in measuring RSSI,too dependent on experience and the positioning of the environment,the complexity of the environment directly affect the positioning accuracy,its universality and applicability is not strong.In this case,we don't consider medium can affect the signal transmission process,the improved BP neural network algorithm is put forward,through C in a real environment of the coordinates of the measured RSSI and the real position,set up an experimental data acquisition system based on ZigBee framework,in PC display and analysis data,the data collection for the back of the system to provide a reliable guarantee.Finally,on the basis of the algorithm,and developed an indoor positioning system,and applied the improved localization algorithm,experimental environment for building the school environment for scenario positioning effect measurement,through the positioning system in this paper,the improved BP neural network algorithm is validated,the positioning accuracy is significantly higher than the traditional algorithm. |
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