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RSS-Based Localization for Wireless Underground Battery-Free Sensor Networks
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DOI：10.1109/LSENS.2022.3212689.png)
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Abstract
En 中文
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.
Keywords:
Sensor signal processing
sensor applications
battery-free sensors
expectation-maximization (EM) algorithm
magnetic induction communication (MIC)
underground localization