摘要
无线传感器网络(WSN)在复杂的山地环境中进行节点定位时,节点部署稀疏会造成定位误差。为此,提出一种WSN节点三维定位算法。根据节点的稀疏程度,融合三维近似三角形内点测试(APIT)算法和DV-Hop算法预估未知节点位置,并搜索邻近节点形成平面,经过未知节点的坐标向平面作垂线,得到垂点坐标的平均值作为未知节点的最终位置。实验结果表明,与APIT算法、DV-Hop算法相比,该算法提高了节点定位精度。
When Wireless Sensor Network(WSN) performs node positioning in complex mountain environments,sparse node deployment can cause positioning errors.Based on the sparseness degree of nodes,the position of an unknown node can be determined by fusing the three-dimensional Approximate Point-in-triangulation Test(APIT) algorithm and the DV-Hop algorithm.By searching neighboring nodes and connecting them,planes could be formed.Then the algorithm makes perpendiculars from the unknown node to the planes,and the average value of the coordinates of perpendicular feet is the final position of the unknown node.Experimental results show that compared with the APIT algorithm and the DV-Hop algorithm,the algorithm improves the node positioning accuracy.
引文
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