**1. Introduction**

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84 Radio Frequency Identification from System to Applications

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Localization of positions and detection of objects is a key aspect in today's applications and, although the topic exists a while ago, it is still under ongoing research. The introduction of global navigation satellite systems (GNSS), particularly GPS [1], and its improvements with accuracies down to a few meters, was a huge step towards ubiquitous localization [2, 3]. This is almost valid for outdoor environments, whereas indoor localization is still a challenging issue [4, 5]. The reason for that is the demanding, dynamic indoor environment, causing severe multipath fading, leading to hard predictable propagation models - thus influencing time, power and phase measurements. However, in the past, much effort has been put into designing high accurate indoor localization systems, including technologies like ultrasonic sound, infrared light, Wi-Fi, Bluetooth, ZigBee, cellular mobile communication (GSM, UMTS), ultrawideband and RFID just to mention a few of them. Despite all the effort, there is no outstanding technology comprising all indoor localization contingencies as every technology in use has its advantages and disadvantages regarding accuracy, availability, complexity and costs.

Due to constantly falling prices of UHF RFID tags [6] additional applications arose beside the traditional concept of radio frequency identification (RFID). Major applications include supply chain technologies [7] and logistics [8], from container level tagging even down to item level tagging [9]. Regarding the Internet of Things [10], UHF RFID has some advantages over other RFID technologies, i.e., LF and HF: UHF RFID tags are small, do not require a battery, allow high data rates and high reading ranges, whereas LF and HF cannot serve with these issues at the same time [10]. Together with the mentioned low costs, the UHF RFID technology may be available in lots of objects (walls, carpets, doors, etc.) in the future. Therefore, indoor posi‐ tioning using UHF RFID technology could be one solution towards ubiquitous localization, as efforts are made to shrink the size of RFID reader ICs and to integrate them into mobile phones.

© 2013 Loeffler and Gerhaeuser; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Loeffler and Gerhaeuser; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The chapter is organized as follows. Section 2 gives a brief overview of today's wireless position‐ ing technologies with a focus on RFID. Section 3 introduces the proposed positioning system and shows the theoretical approach along with an example. Section 4 focuses on challenges and limitations of the system and Section 5 presents results from measurements carried out underlin‐ ing the principle of operation. Section 6 provides a discussion based on the results. Finally, Section 7 gives a short summary and concludes with a perspective for future work.

value of the measurement values. *x*

the estimated values *x*

measurement.

^ describes the random variable of the measurement process,

Localizing with Passive UHF RFID Tags Using Wideband Signals

http://dx.doi.org/10.5772/53769

87

¯ is the mean value of the true values.

*<sup>k</sup>* - *xk* )<sup>2</sup> (4)

whereas E{⋅ } is the corresponding expectation value. In the following, the standard deviation

**Rightness** or trueness describes how well the measured values respectively the expectation of

The rightness is a measure for the average discrepancy between a measured and a reference

**Accuracy** takes both, the precision and the rightness, into account. In fact, only high accuracy may be achieved if precision and rightness is high, too. A well known definition of the accuracy

^ - *<sup>x</sup>*)2} and RMSE ^ <sup>=</sup> <sup>1</sup>

RMSE ^ describes the estimated RMSE of the measurement and *xk* the true value at the the *k*th

Equation (5) shows that a distorted measurement with a high precision may be more accurate than an undistorted measurement with a low precision respectively standard deviation.

According to [11] the first expression in Equation (4) can be transformed into

RMSE= *σ<sup>x</sup>*

^ fit to the expectation of the true values *<sup>x</sup>*, i.e., a so called bias with

*Bias E x E x Bias x* = - = - =- { } {} *x x* ˆ ˆ and · *<sup>x</sup>*<sup>ˆ</sup> (3)

*<sup>N</sup>* ∑ *k*=1 *N* (*x* ^

<sup>2</sup> + Bias<sup>2</sup> (5)

*σx* is used as a measure for the precision of a positioning technique.

Bias ^ is the estimated rightness of the measurement and *<sup>x</sup>*

is the root mean square error RMSE, which is defined as

RMSE= MSE= E{(*x*

**Figure 1.** Example of trilateration with RFID reference tags

value and may be described as bias or offset.
