| As one of the research topics in the field of science and technology,wireless sensor network technology has attracted more and more attention.The most widely used is the positioning technology in wireless sensor networks.Due to the influence of environmental factors on indoor positioning,the positioning accuracy will be greatly reduced.In order to improve the positioning accuracy,it is necessary to optimize from the aspects of enhancing the ranging accuracy and improving the centroid positioning algorithm.Based on the research of RSSI ranging model,in order to enhance the accuracy of ranging,a hybrid filtering algorithm combining single filtering advantages is proposed.At the same time,aiming at the dependence of the parameter values on the environment in the RSSI ranging model,an algorithm for dynamically updating the parameters of the ranging model is proposed,so that the wireless sensor network node can adapt to the external interference and update the current environmental parameters in time to achieve accurate ranging.On this basis,an improved centroid localization algorithm is proposed.On the one hand,by increasing the density of beacon nodes,a sub-region localization algorithm is proposed;on the other hand,the weight coefficients are modified to improve the positioning accuracy.Finally,the ZigBee-based wireless sensor network positioning system is designed and implemented.The hybrid filtering,dynamic update model parameters and improved sub-region weighted centroid localization algorithm are experimentally verified.In addition,while implementing the above experimental system,the effects of dynamic update model parameter algorithm and linear regression fitting algorithm,traditional centroid localization and sub-region weighted centroid localization algorithm on the localization result are analyzed by MatLab simulation.The simulation results show that the improved centroid localization algorithm has higher positioning accuracy and stability. |
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