| GPS and other global positioning technology makes positioning services takes part in people's daily lives,especially the mobile app basically integrated positioning capabilities to provide peripheral service information.With the development of social live,people need more accurate positioning to find the surrounding information when they are indoor.However,.GPS signals are often difficult to locate indoors through buildings.Therefore,indoor positioning technology has become a hot research topic nowadays.This paper firstly compares the characteristics and common algorithms of different indoor location technologies and finally determines to use RSSI value of iBeacon Bluetooth signal as the basis to realize the indoor location,which is mainly divided into two stages,the first one is the ranging and the second one is locating.This article has been improved from these two aspects,the following are the main tasks:1.In order to measure the signal strength under each distance,the same point needs to be sampled several times.Due to the signal fluctuation,the Gaussian filter is firstly used to reject the interference signal and then the Kalman filter algorithm is used instead initially subtracting small ranging error.2.The use of BP neural network to fit the signal ranging model,compared with the traditional logarithmic distance loss model,to avoid the estimation of parameters,reducing the cumulative error.The results of ranging experiments show that the proposed method not only reflects the local fluctuation of RSSI value with RSSI value,but also realizes the signal propagation in complex indoor environment.3.On the basis of distance measurement,we use the weighted triangular centroid location algorithm to calculate the coordinates of the node to be located,and improve the selection of the weight of the algorithm,which gives more weight to the nodes closer in distance.The experimental results show that,Improved algorithm to improve the positioning accuracy of 20%,with practical value. |
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