Research On WSN Node Location Algorithm Based On RSSI

With the rapid development of Internet of Things technology,wireless sensor networks(WSN)have become more and more widely used in military,medical,disaster relief and other fields.Node location technology is a key technology in the WSN field,and it is vital to the data transmission of the entire WSN.In practical applications,considering the cost issue,GPS positioning systems cannot be installed on all nodes,so the positioning of unknown nodes requires a certain amount of known nodes to participate.Node positioning includes a ranging phase and a positioning phase.This paper improves the node positioning algorithm in two phases to improve the positioning accuracy of the node.In the positioning stage,this paper proposes an RSSI centroid positioning algorithm(PSO-DE-RSSI)optimized by chaotic particle swarms and differential evolution.The algorithm first finds the three anchor nodes closest to the unknown node through the RSSI ranging model,and uses the unknown node coordinates as parameters to construct the fitness function.Then based on the particle swarm algorithm,the differential evolution algorithm is introduced,and the chaotic search mechanism and dynamic inertia weight are added.Finally,the coordinates of the unknown node can be roughly determined by the global optimal solution of the algorithm.The PSO-DE-RSSI algorithm combines the advantages of simple parameter setting of particle swarm algorithm,faster search speed and strong global search ability of differential evolution algorithm,which effectively reduces the positioning error of nodes.The simulation experiment results show that the PSO-DE-RSSI algorithm has a certain improvement in positioning accuracy compared to the particle swarm optimization RSSI centroid positioning algorithm(PSO-RSSI)and the weighted centroid positioning algorithm based on RSSI.In the ranging phase,the data information sent by the anchor node will be affected by environmental factors such as multipath fading and obstacles,which results in data distortion when the measured value is converted into a distance value.This paper improves the traditional Gaussian filtering algorithm and proposes a weighted Gaussian filtering algorithm based on median.The algorithm first filters the collected multiple RSSI values,and uses Gaussian filtering algorithm to eliminate abnormal RSSI values.Then use the effective robustness of the median value to weight each RSSI value to reduce data fluctuations.Finally,the RSSI value is converted into distance to complete the distance measurement between nodes.Simulation experiment results show that compared with other filtering algorithms,this algorithm effectively reduces the positioning error in the ranging stage.In this paper,the algorithms of the positioning phase and the ranging phase are improved and combined,and the node positioning accuracy has been improved to a certain extent.