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An indoor gas leakage source localization algorithm using distributed maximum likelihood estimation in sensor networks

机译:在传感器网络中使用分布式最大似然估计的室内气体泄漏源定位算法

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摘要

Gas leakage source localization based on sensor networks has an important practical significance in many fields such as environmental monitoring, security protection and pollution control. This paper proposed a gas leakage source localization algorithm using distributed maximum likelihood estimation method for mobile sensor network to improve the lower performance with static sensor network. Firstly, the likelihood function of gas leakage source parameters was deduced based on the gas turbulent diffusion model. Then, the parameters of gas leakage source were estimated based on the likelihood function with the gas concentration measurement in environment. Finally, the gas leakage source location would be achieved through the iterative optimization of the likelihood function. The preliminary experimental results show that the proposed distributed Maximum Likelihood Estimation method could be achieved an acutely gas leakage source location in an indoor environment. And the reasonable path planning and dynamic topology changing could improve the positioning performance.
机译:基于传感器网络的气体泄漏源定位在环境监测,安全保护和污染控制等许多领域具有重要的现实意义。提出了一种基于分布式最大似然估计的移动传感器网络气体泄漏源定位算法,以提高静态传感器网络的性能。首先,基于气体湍流扩散模型推导了气体泄漏源参数的似然函数。然后,利用环境函数中的气体浓度测量值,根据似然函数估算出气体泄漏源的参数。最后,将通过似然函数的迭代优化来实现气体泄漏源的位置。初步的实验结果表明,所提出的分布式最大似然估计方法可以在室内环境中实现急性漏气源定位。合理的路径规划和动态拓扑变化可以提高定位性能。

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