一种降低传感器网络边界定位误差的方法
首发时间:2009-04-17
摘要:质心定位方法是一种非常有效且资源有限的定位算法。在质心定位算法中,一个传感器节点的定位精度主要依赖于此传感器节点收到的不同的信标节点的位置的数量。在节点传输范围比较小的网络中,定位误差在整个网络中表现为比较平衡,但在节点传输范围比较大的网络中,定位误差就很不稳定,且在网络的边界区域会增大。基于上述原因,本文提出了一种新的算法——边界修正质心定位算法(CLwWC),用来有效地降低网络边界的定位误差。
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A method of decreasing the localization error in border areas of sensor networks
Abstract:The centroid localization scheme is a very efficient and re-source aware algorithm to estimate a position. On a sensor node, the precision of the position depends on the number of different beacons positions the node receives. In networks with a small transmission range, the localization error behaves very balanced over the whole network. But in very large sensor networks with high transmission ranges, the localization error behaves very unsteady and is increased in most border regions of the network. Based on above reason, this paper presents a new algorithm Centroid Localization with Edge Correction (CLwEC) to decrease the localization error in border regions of a network significantly.
Keywords: Resource Aware Localization Sensor Networks Correction of Positions Localization Error
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