An exponential rayleigh model for rss-based device-free localization and tracking
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This document proposes an Exponential-Rayleigh (ER) model for device-free localization and tracking using wireless sensor networks. The ER model accounts for both the large-scale exponential attenuation of signals and the small-scale enhancement of signals from target-induced multipath components modeled by a Rayleigh distribution. Experimental results show the ER model outperforms existing models by mitigating multipath interference effects and improving localization and tracking performance.
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An exponential rayleigh model for rss-based device-free localization and tracking
- 1. An Exponential-RayleighModelfor RSS-BasedDevice-FreeLocalization and Tracking Abstract: A common technical difficulty in device-free localization and tracking (DFLT)with a wireless sensornetwork is that the change of the received signal strength (RSS) of the link often becomes more unpredictable due to the multipath interferences. This challenge can lead to unsatisfactory or even unstable DFLT performance. This work focuses on developing a new RSS model, called Exponential-Rayleigh (ER) model, for addressing this challenge. Based on data from our extensive experiments, we first develop the ER model of the received signal strength. This model consists of two parts: the large-scale exponential attenuation part and the small-scale Rayleigh enhancement part. The new consideration on using the Rayleigh model is to depict the target-induced multipath components. We then explore the use of the ER model with a particle filter in the context of multi- target localization and tracking. Finally, we experimentally demonstrate that our ER model outperforms the existing models. The experimental results highlight the advantages of using the Rayleigh model in mitigating the multipath interferences thus improving the DFLT performance.