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-to-noise 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.