基于传感器网络的气体源定位方法研究

提出一种分层结构的自组织无线传感器网络(WSN)用于气体污染源的定位研究,可以广泛应用于反恐、环境监控等场景。在修正的气体污染源浓度衰减模型基础上,提出一种改进的非线性最小二乘算法(I-NLS)以及极大似然算法(MLE)用于气体污染源定位。仿真试验对比研究了两种算法在不同的传感器节点以及背景噪声情况下对预估定位误差的影响。试验结果表明了这种分层结构的WSN用于气体污染源定位是可行的,同时验证了I-NLS、MLE两种算法定位的有效性。

Study of Plume Source Localization Based On WSN

A hierarchical wireless sensor networks (WSN ) was proposed to estimate the plum source location, which could be widely used in terrorist attacks and environment monitoring. The improved nonlinear least squares ( I-NLS ) location algorithm and the maximum likelihood estimation (MLE) location algorithm were used based on the WSN. The effect of the estimation error, with different sensor number and different background noise, was researched by simulations. The final results show that the proposed WSN is feasible and the two location algorithms are effective, and the two algorithms have their own advantages in different situations respectively.