دانلود رایگان مقاله محلی سازی device-free انرژی کارآمد

Abstract

A Device Free Localization (DFL) system can locate and track people wearing no wireless devices, due to the fact that a person standing at different locations attenuates wireless links differently. Since the DFL system usually consists of battery-powered sensors, energy efficiency is a critical issue. However, existing works mainly focus on improving localization accuracy by designing various metrics to characterize wireless link attenuation, and none of them considers energy efficiency, specifically. We present EE-Loc, an energy efficient localization system, for locating and tracking people with higher energy efficiency and comparable localization accuracy compared to the state-of-the-art DFL systems. EE-Loc has two main energy efficient components. First, EE-Loc has a radio tomographic imaging (RTI) component that uses only one bit information to describe link attenuation. The one bit information is derived from the Kullback–Leibler divergence (KL-divergence) of Received Signal Strength (RSS), and we prove that RTI with this one bit information is sufficient for localization. Second, EE-Loc has a tracking component that deactivates many unnecessary links through predicting the person’s location with Kalman filter to reduce energy consumption. We build a test-bed of EE-Loc using 16 sensors. The experimental results indicate that EE-Loc improves energy efficiency by 27.05% compared to Spin*> for locating a person, and reduces link measurements by 41.91% for tracking a person, without compromising the localization accuracy.

7. Conclusions

In this paper, we propose EE-Loc to locate and track a person in the surveillance area. By reducing the payload of packets with a new RSS dynamic measure KLDB and deactivating unrelated links with Kalman filter, we improve the energy efficiency of DFL systems. Two experiments are conducted in both indoor and outdoor environments. The indoor experiment shows that the localization accuracy of EE-Loc is comparable to the state-of-the-art while reducing the length of packet payload. With the payload reduction, EE-Loc improves the energy efficiency of DFL systems by 27.05% compared with Spin∗>. In the outdoor experiment, EE-Loc further reduces the necessary link measurements in a round by 41.91%. In our future work, we will consider multiple target tracking with EELoc, as well as investigate our system for localization and tracking in more challenging indoor and outdoor scenarios, where foreign obstacles are included inside the surveillance field.