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Abstract
Indoor localization, this means solutions providing the position of mobile objects/persons in indoor environments (e.g., hospitals, malls, etc.), is one of the most cutting-edge services with growing demand in smart applications such as robotics for care, pedestrian navigations, etc. With the objective of providing indoor localization, this paper presents the experimental analysis of simultaneous radio frequency measurements from two different radio frequency systems: Ultra High Frequency Radio Frequency IDentification (UHF RFID) and macrocellular networks. Extensively deployed cellular technologies (Global System for Mobile communications (GSM) and Universal Mobile Telecommunications System (UMTS)) are here evaluated with the purpose of enhancing pre-existent RFID-based localization systems at reduced costs. Temporal and statistical analysis of the measurements gathered from each technology is performed, and its applicability for localization is assessed. Based on this analysis, a RFID localization mechanism that is able to integrate macrocellular technologies information is proposed, showing improved results in terms of accuracy.
Highlights
1 Introduction Several radio frequency-based systems have been proposed for providing indoor localization such as Ultra Wide Band (UWB), which presents location errors of few centimeters or Radio Frequency IDentification (RFID), which is in the range of few meters
Mechanisms for opportunistic radio positioning based on multiple techniques (e.g., wireless local area network (WLAN) together with Global System for Mobile communications (GSM), etc.) have been devised as promising solutions [1]
The accuracy is much lower than RFID-based systems
Summary
Several radio frequency-based systems have been proposed for providing indoor localization such as Ultra Wide Band (UWB), which presents location errors of few centimeters or Radio Frequency IDentification (RFID), which is in the range of few meters. The proposed option of combining UHF RFID tags with macrocell technology measurements could successfully provide the level of accuracy required in RFIDbased localization systems for pedestrian navigation in buildings. It will focus on indoor navigation in a floor of a building such as hospitals, universities, city halls, etc. ∀i∈I ð9Þ where p^ðμPrxi jγf Þ is the probability density function (PDF) of the conditional probabilities for each candidate position, γf, and tag i This PDF is estimated assuming a normal distribution (a common approach for modeling the received power) with mean and standard deviation in base of the samples gathered in the calibration phase Its weight is calculated as the distance between such vector and the one formed from the current received power levels μPrx( γcurr) gathered by the localized platform: wðγf ; γcurrÞ 1⁄4 d μPrxðγf Þ; μPrxðγcurrÞ
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