基于权重重心法的传感器网络节点定位

Localization for Sensor Networks Based on Weighted-Centroid

传感器网络是由大量廉价的、低功耗的、随机布置的、无人值守的、具有有限的无线通信能力的多功能微小传感器节点组成的。传感器网络的这些固有特性使得节点定位变得十分困难。为了减小传感器网络节点定位误差、提高定位算法对测距噪声的鲁棒性、降低算法的复杂性,提出了一种只需利用少量信标节点位置信息和未知节点与信标节点间的测距估算未知节点位置的分布式节点定位算法,这种算法使用角度权重函数、权重多边形和循环组合三边测量法等手段以避免使用奇异信标节点信息。仿真结果表明:与其它同类算法相比,这种算法具有定位精度高、对测距噪声鲁棒性好、低计算复杂性和低通信开销等优点。

Sensor networks are composed of a large number of low - cost, low - powered, randomly deployed, unattended, radio range - limited and multi - functional micro sensor nodes. The inherent characteristics make it very difficult to locate unknown nodes in the networks. In this paper, a distributed algorithm using few locations of anchor nodes and range measurement between unknown node and an anchor node is presented in order to reduce the localization error, improve the robustness to the range measurement noise, and lower the computational complexity. This algorithm utilizes angular weighted function, weighted polygon and alternatin~ combination trilateration methods to avoid using anchors＇ outlier information. Simulations have verified its accuracy, robustness with respect to range measurement noise, low complexity and low communication overhead compared to other similar algorithms.