RSS-Based Localization for Wireless Underground Battery-Free Sensor Networks

被引：3
|
作者：
Gu, Hongzhi [1 ]
机构：
[1] Norfolk State Univ, Dept Engn, Norfolk, VA 23504 USA
来源：
IEEE SENSORS LETTERS | 2022年 / 6卷 / 10期
基金：
美国国家科学基金会;
关键词：
Sensor signal processing; sensor applications; battery-free sensors; expectation-maximization (EM) algorithm; magnetic induction communication (MIC); underground localization;
D O I：
10.1109/LSENS.2022.3212689
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Underground battery-free sensors do not require battery replacement that can support large-scale deployment for agriculture applications. The underground environment is dynamic, and the soil permittivity and electric conductivity vary significantly due to precipitation and irrigation. These dynamic parameters affect the accuracy of underground battery-free sensor localization. This letter proposes a localization framework using the expectation-maximization algorithm by considering the signal attenuation coefficient as a latent variable. The proposed solution is evaluated collected by underground sensors. Simulation results show that the root mean square error is around 0.3 m in various scenarios.
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页数：4
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