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76 Mohammad Heidari and Kaveh Pahlavan
localization applications, and the emerging 3D channel models developed for
smart antenna applications [9] might be used for modeling the AOA for RFID
localization. However, the available wideband indoor multipath channel measurement
data and models presented in [2] are not suitable for analyzing the
behavior of TOA and TDOA for localization applications.
The availability of several different RFID localization techniques employing
different signal metrics provides the designer with various options to suit the
specific application [10]. However, the ability to empirically evaluate the performance
of a chosen RFID localization system configuration is important to
successful design and deployment.
In this chapter we will introduce a novel real-time testbed for comparative
performance evaluation of RFID localization systems, which can assist the system
designer in evaluating the performance in a specific indoor environment. In the
remainder of the chapter first we will provide an overview of indoor localization
systems, their metrics, and their respective accuracies. Then we will provide a
detailed description of the testbed and some performance evaluation results with
emphasis on WiFi RFID localization in an indoor environment.
6.2 Fundamentals of RFID localization
The basic concept of any positioning system is illustrated in Fig. 6.1. The locationsensing
devices measure the distance-related metrics, between the RFID device
and a fixed reference point (RP), such as TOA, AOA, RSS, or TDOA. The
positioning algorithm processes the reported metrics to estimate the location
coordinates of the RFID tag. The display system exhibits the location of the
mobile terminal to the user. The accuracy of the location estimation is a function
of the accuracy of the location metrics and the complexity of the positioning
Fig. 6.1 A basic block diagram of a positioning system.