基于精细化梯度的传感器网络节点距离测量

定位在无线传感器网络中具有极其重要的作用,而距离测量往往是定位的前提、寻求低成本、低开销、高精度的分布式传感器网络节点距离测量算法是本文的主要目的.根据无线传感器网络最小跳数梯度场中节点精细化梯度值的分布特征,提出了一种基于精细化梯度的传感器网络节点距离测量方法DV-FGI.与DV-hop算法相比,DV-FGI保留了DV-hop算法低成本、低开销的优点,具有更高的测量精度,并将节点距离测量分辨率从节点有效通信半径提高至网络节点间距.理论分析及仿真结果表明,该算法在节点密集分布的无线传感器网络中具有很好的效果.

Distance Estimating Algorithm Based on Fine-grain Gradient in Wireless Sensor Networks

Locali}ation takes an important role in wireless sensor networks, while distance measuring is usually the precondition of tracking or positioning. Finding a distance-measuring algorithm with low cost, low overhead and high precision is the main intension of this paper. In this paper, derived from the distributing characteristics of node's fine-grain gradient value in wireless sensor networks' minimum hop gradient field, a way based on the fincgrain gradient to estimate the distance between nodes, namely DV-FGI, was presented. Compared with the DV-hop algorithm, the measuring precision of DV-FGI is improved largely at the nearly same cost and overhead, and the resolution ratio of measuring is improved from communication radio range to the distance interval between neighbor nodes. "hhe theoretical analysis and simulation results validate that the method is cauite effective in the wireless sensor networks deployed with dense nodes.