Research On Wireless Sensor Network Location Algorithm Based On DV-Hop

Wireless sensor networks are used in many fields,and positioning technology is the most critical technology in wireless sensor networks.Therefore,positioning systems and algorithms designed for the characteristics of wireless sensor networks have become a research hotspot in the field of wireless sensor networks in conjunction with application requirements.The main content of the research includes the following aspects:First,the research status of wireless sensor network positioning technology is described,and typical ranging and non-ranging positioning algorithms are described in detail.By analyzing and comparing the advantages and disadvantages of several typical positioning algorithms,a wireless sensor positioning algorithm based on DV-Hop is proposed.Secondly,the principle of the classic DV-HOP algorithm is elaborated and a brief analysis of the errors generated,then the intelligent swarm algorithm fruit fly algorithm is briefly introduced,and it is improved and analyzed,and finally the improved DV-HOP positioning algorithm is proposed On the one hand,the jump-hopping mechanism is added in the first stage of DV-Hop;on the other hand,the improved fruit fly algorithm is used in the third stage of DV-Hop to replace the maximum likelihood method to optimize the coordinates of unknown nodes.Finally,through Matlab simulation,the results show that the improved DV-Hop algorithm in this paper is significantly better than the traditional DV-Hop algorithm and the improved particle swarm algorithm DV-Hop algorithm.Finally,according to the actual needs of node positioning,combined with improved algorithms,a WSN positioning system based on Zigbee was designed,and the software and hardware modules of the system were designed respectively.Finally,the actual test of the designed WSN positioning system is conducted The results show that the average error of the traditional DV-Hop positioning algorithm is 2.55 m,and the average error of the improved positioning algorithm is about 1.02 m.It is effective in indoor environment and can be applied to indoor positioning.Figure[51]Table[14]Reference[62]...