关键词: 无线传感器网络, 指纹定位, 模糊属性, 多维高斯模型, 相似度

Abstract: Currently wireless sensor network localization algorithms can hardly meet people’s requirements of positioning accuracy and computational complexity at the same time. A multidimensional Gaussian approximation based algorithm is proposed to deal with the dilemma. According to the received signal strength map, the algorithm establishes the fuzzy attribute matrix between the reference points and the unknown node, then sets an ideal point and calculates its attribute coordinates. After that, the distance relationship of the ideal point and the different reference points is estimated based on the multidimensional Gaussian model. Then an adjustment function is introduced to amend the position deviation between the ideal point and the unknown node. And the similar degree between different reference points and the unknown node is calculated for positioning. The algorithm has a simple operation process and the experimental results show that the accuracy of the positioning result is high and the error fluctuation range is small.

Key words: wireless sensor network, fingerprint localization, fuzzy attribute, multidimensional Gaussian model, similar degree