As a new technology of information acquisition and processing, the wireless sensor network (WSN) can sense, collect and process a variety of data and information about the target through a colaborative approach in the monitoring area. The node localization technology works as one of the core support technologies of WSN and it is the basis and premise of target recognition, localization, tracking and many other applications. Therefore, the research of high accuracy localization algorithm for WSN has important theoretical significance and applied value.In the paper, we design localization algorithms since the positioning accuracy of the existing wireless sensor network node localization algorithm is not high. We propose an improved weighted centroid localization algorithm and an improved DV-Hop localization algorithm respectively since the accuracy of the centroid localization algorithm and the DV-Hop localization algorithm is not high. The main research work and innovation points of this paper are listed as follows:(1) A centroid localization algorithm based on RSSI weighted fusion is proposed:use every three beacon nodes which are distant from the unknown node near to far to compose of a triangular positioning unit. Use the traditional centroid algorithm to calculate the centroid. Then make all the centroids which are calculated from each positioning unit to compose of a polygon. After that, analyze the factors which affect the weights of each vertex, and determine the weight of each factor. Finally use weighted centroid localization algorithm to calculate the centroid of the polygon and get the final coordinate of the unknown node.(2) An improved DV-HOP localization algorithm based on quantum particle swarm optimization algorithm with adaptive mutation is proposed:Since the positioning error of DV-Hop algorithm is mainly from the estimated value of the average distance per hop of beacon nodes in the network, we improve the method of calculating the average hop distance values by processing the error of the average hop distance values in the paper. It makes the estimated value of the average hop distance of the unknown node more accurate. Then use the improved particle swarm optimization algorithm to find the optimal localization quickly by way of iterative calculation. It makes the estimated position of the unknown node closer to the true position.The simulation results show that the positioning performance of the two improved algorithms has obvious improvement. The improved weighted centroid algorithm has obvious positioning advantage when the beacon nodes are uneven distributed, and it overcomes the issue that the traditional centroid algorithms have large positioning error in this environment. The improved DV-Hop algorithm significantly reduces the positioning error of the unknown node. It improves the positioning accuracy and stability of DV-Hop algorithm. |