Research On WSN Node Positioning Based On Swarm Intelligence Algorith

The wireless sensor network can process the data information and convert the external information received by the sensor node according to the external feedback,forming the exchange and transmission of data.Among them,node location technology,as a hot research and development nowadays,is applied in various scenarios,responsible for a series of functions such as target location tracking and identification,and has the advantages of simple deployment level,low cost and energy consumption,and is currently widely studied by scholars.This paper mainly studies the DV-Hop location algorithm in node location technology,analyzes the factors causing errors,and then optimizes and improves the causes.The main work is as follows:(1)To improve the traditional gray Wolf optimization algorithm,the improvement mainly lies in the adoption of dynamic inertia weight factor and adaptive search adjustment strategy,the Wolf contribution degree and fitness are compared,and then choose a better position update formula,so as to improve the algorithm’s searching accuracy.(2)Analyzed the influence of the communication radius to the Hop,resulting in DV-Hop error,the positioning precision of localization algorithm by changing the traditional single communication radius Settings,resetting to double communication radius,make the returned to jump between the unknown node and beacon node value into is no longer a pure integer,but the integer plus communication radius R,so that the estimated distance closer to actual value.(3)In the last step of the traditional DV-HOP algorithm to calculate the unknown node position,the traditional matrix equation is changed,and the improved gray Wolf algorithm is used to replace the conventional calculation method to find the optimal value.