This research investigates the impact of multipath signals in UWB communications and explores their potential to improve localization accuracy of tags using the additional information captured in the Channel Impulse Response (CIR). While traditional localization typically relies on multiple anchors, this study focuses on using a single anchor and creating multiple Virtual Anchors (VAs) through MultiPath Components (MPCs). The research proposes algorithms such as likelihood, algebraic, and fminsearch methods, and tests their performance through simulations in environments with anchors, tags, and reflective surfaces. After confirming the feasibility of using reflection multipath signals for localization through the simulations, experiments were conducted with NXP's SR150 UWB tags, which collect CIR data via two antennas. An indoor environment was set up with two MPCs and a strategically placed anchor. Data was collected from various tag locations and analyzed using the different localization methods. The collected CIR data revealed additional reflections, notably from the ceiling and ground, which sometimes interfered with the desired MPC reflections. To address this, data cleaning techniques were implemented for the likelihood method, and the two antennas were used to approximate the AoA in the fminsearch and multilateration methods. The final results demonstrated that the likelihood method achieved an average localization error of 26 cm, the fminsearch method 20.7 cm, and the algebraic method 24 cm. While the fminsearch method provided the best accuracy, it required data from two antennas, unlike the likelihood method, which only needed one. The fminsearch method showed improved accuracy near MPCs, though its performance declined as the tag moved further away. This suggests its potential for applications where AoA is large, as traditional methods become less accurate beyond 60-degree angles.