Research On Improved Optimization Algorithm For Wireless Sensor Network Positioning Based On RSSI

With the rapid development of sensor technology and Internet of Things technology,wireless sensor networks have been widely used.Its applications in military reconnaissance,target tracking and intrusion monitoring need to determine the location of nodes,and positioning technology has become one of the research hotspots.The existing centroid positioning method based on Received Signal Strength Indication(RSSI)has the problem of large centroid estimation error.Therefore,it is necessary to optimize the centroid estimation and error correction to improve the positioning accuracy.The RSSI-based centroid positioning algorithm is optimized in terms of centroid estimation and error correction.The RSSI-based differential correction weighted centroid positioning algorithm and the RSSI-based gray wolf optimization differential correction centroid positioning algorithm are proposed,and the performance of the proposed algorithm is verified by simulation.The specific research content includes:(1)Analyze the research background and significance of wireless sensor network and positioning technology and the current research status,and creatively classify the existing positioning algorithms,analyze the existing problems of the existing positioning algorithms,and propose related solutions.(2)A differential correction weighted centroid location algorithm based on RSSI is proposed.Based on the traditional centroid positioning algorithm,the distance selection system is optimized to reduce the number of centroids to be solved in order to solve the problem of large calculation of centroids in traversal;use the centroid with the closest distance as the reference node to optimize the difference correction factor to correct the centroid coordinates;The reciprocal of the measured distance corresponding to the centroid is defined and used as the weight of the centroid,the coordinates of unknown nodes are estimated by weighted centroid,and the simulation comparison with the traditional centroid positioning algorithm verifies the effectiveness of the proposed algorithm in improving the accuracy of node positioning.(3)A gray wolf optimized differential correction centroid location algorithm based on RSSI is proposed.The algorithm is divided into preliminary positioning and precise positioning.The preliminary positioning of unknown nodes is achieved through the differential correction centroid positioning algorithm.The result of the preliminary positioning is used as the initial value of the gray wolf optimization algorithm.The fitness value of the centroid is calculated to define the gray wolf level.Global search,local search and iterative location update to achieve precise positioning of unknown nodes.Simulation experiments show that compared with traditional positioning algorithms,the positioning effect and stability have been effectively improved.This paper optimizes the node positioning algorithm of wireless sensor network to improve the accuracy of node positioning,promotes the development of wireless sensor network node positioning technology,and provides theoretical support for the wide application of wireless sensor network positioning system.