In this paper, we present a 5.8 GHz RFID tag equipped with a high gain, low power reflection amplifier based on a tunnel diode. Experimental results show that the realized prototype achieves gains above 40 dB and requires only 29 μW of biasing power. The tag detects very low RF signals (< -90 dBm) and provides read ranges up to 2 km. Long communication ranges and Manchester encoding are achieved by biasing on and off the tunnel diode.

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Localization and tracking (L&T) are some of the most important applications of radio frequency identification (RFID) technology. One method of achieving this is by approximating the position of an object from the measured backscattered signal parameters and backscattered data. A comprehensive analysis of the backscattered signal parameters, such as received signal amplitude and phase, is necessary to establish their effect on the accuracy of L&T. In this context, this paper investigates the probability density functions (PDFs) of the received signal amplitude and phase for RFID systems. It was observed that both PDFs converge to Gaussian distributions in high signal-tonoise ratio scenarios. Moreover, the Cramer Rao Lower Bound (CRLB), which serves as an established reference for unbiased estimation, is also derived for the estimated received signal amplitude and phase difference. It was noticed that the CRLBs are inversely proportional to the number of observations taken for the parameter estimation. Finally, it is pertinent to mention that if multiple types of sensed information are fused to perform L&T, it results in millimeter-level accuracy. For RFID, one such technique which employs multiple sensed parameters for L&T is Hybrid Inertial Microwave Reflectometry (HIMR). This paper also presents a simulation and experimental analysis of HIMR. HIMR-based RFID tracking scheme results in tracking accuracy in the range of 1-10 mm.

The estimator showed good convergence for the y-coordinates except slight divergence between 0.8-1.15 s possibly because the actual y curve started changing its slope. . . .

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