Radio Frequency IDentification (RFID) has been increasingly used to identify and track objects automatically. RFID has also been used to localize tagged objects. Several RFID localization schemes have been proposed in the literature; some of these schemes estimate the distance between the tag and the reader using the Received Signal Strength Index (RSSI). From a theoretical point of view, RSSI is an excellent approach to estimate the distance between a sender and a receiver. However, our experiments show that there are many factors that influence the RSSI value substantially and that, in turn, has a negative effect on the accuracy of the estimated distance. Another approach that has been recently proposed is utilizing transmission power control from the reader side. Our experiments show that power control results are more stable and accurate than RSSI results. In this paper, we present a test-bed comparison between the power control and the RSSI distance estimation approaches for active RFID tags. We also present the Angle of arrival Cluster Forming (ACF) localization scheme that uses both the angle of arrival of the tag's signal and the reader's transmission power control to localize active tags. Our experiments show that ACF is very accurate in estimating the location of active RFID tags.

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Reliable and energy-efficient reading of Radio Frequency IDentification (RFID) tags is of utmost importance, especially in mobile and dense tag settings. We identify tag collisions as a main source of inefficiency in terms of wasting both medium access control (MAC) frame slots and reader's energy. We propose modulation silencing (MS), a reader-tag interaction framework to limit the effect of tag collisions. Utilizing relatively simple circuitry at the tag, MS enhances the performance of existing anti-collision protocols by allowing readers to terminate collision slots once a decoding violation is detected. With shorter collision slots, we revisit the performance metrics and introduce a new generalized time efficiency metric and an optimal frame selection formula that takes into consideration the MS effects. Through analytical solutions and extensive simulations, we show that the use of MS results in significant performance gains under various scenarios.

Small and pervasive devices have been increasingly used to identify and track objects automatically. Consequently, several low-cost localization schemes have been proposed in the literature based on angle of arrival (AoA), time difference of arrival (TDoA), received signal strength indicator (RSSI) or their combinations. In this paper, we propose a three-dimensional empirical AoA localization (TDEAL) technique for battery-powered devices. The proposed technique processes the AoA measurements at fixed reader nodes to estimate the locations of the tags. The proposed technique provides localization accuracy that mitigates non-linear empirical errors in AoA measurements. We utilize two omni-directional antenna arrays at each fixed reader node to estimate the location vector. With multiple location estimations from different fixed reader nodes, each estimated location is assigned a weight that is inversely proportional to the AoA phase-difference error. Furthermore, the actual AoA parabolic formula of the location is approximated to a cone to simplify the location calculation process. The proposed localization technique has a low hardware cost, low computational requirements, and precise location estimates. Based on the performance evaluation, significant location accuracy is achieved by TDEAL; where, for instance, an average error margin of less than 13 cm is achieved using 10 readers in an area of   10   m ×   10   m . TDEAL can be utilized to provide reference points when integrated with a relative (e.g., inertial navigation systems) localization systems.