Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (11): 80-83.

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Location method based on DBSCAN in wireless sensor networks

ZHU Xuanzhang   

  1. Center of Educational Technology, Hunan University of Science and Engineering, Yongzhou, Hunan 425100, China
  • Online:2013-06-01 Published:2013-06-14



  1. 湖南科技学院 现代教育技术中心,湖南 永州 425100

Abstract: Under the NLOS(Non-Line-Of-Sight) propagation environments, in order to achieve better location performance, a localization method based on DBSCAN in wireless sensor networks is proposed in this paper. The TOA(Time Of Arrival) from the unknown node is measured by many sensor nodes, then the weighted least squares estimation algorithm is used after data packet processing. According to multiple measurements and estimations, the DBSCAN(Density-Based Spatial Clustering of Applications with Noise) is used to tick off the bad location results to mitigate the location error. The experimental simulations have done. Simulation results show that the proposed location method can restrain the location error effectively and get the precise position of the unknown node, can improve the location accuracy than traditional methods.

Key words: wireless sensor networks, location, sensor node, Density-Based Spatial Clustering of Applications with Noise(DBSCAN), Non-Line-Of-Sight(NLOS)

摘要: 在NLOS传播环境下,为了获得更好的定位性能,由多个已知传感器节点测量来自未知节点的电波到达时间TOA,对TOA测量数据进行分组处理和加权最小二乘估计进而获得未知节点的初步定位结果,依据多次测量和估计并采用DBSCAN进行聚类处理从而剔除坏点获得较小的定位误差,实现了对未知节点的精确定位,最后进行实验仿真。计算机仿真结果表明所提出的定位方法能有效地抑制NLOS误差,具有较小的定位误差,鲁棒性较强,并较其他传统定位法进一步提高了定位精度。

关键词: 无线传感网, 定位, 传感器节点, 基于密度的加噪空间聚类应用算法(DBSCAN), 非视距传播