Ultra-wideband (UWB) positioning is highly susceptible to environmental factors, whereas inertial navigation system (INS) positioning suffers from cumulative errors over time. To address these limitations, this paper investigates the fusion of UWB and INS positioning techniques to increase the positioning accuracy. This study provides a comprehensive analysis of UWB and INS positioning principles and presents a novel approach for their integration. In the experimental setup, the time of arrival (TOA) method was employed for UWB positioning evaluation, and separate experiments were conducted to assess the performance of the INS system. The experimental results confirm that UWB positioning is prone to environmental disturbances, causing interruptions in continuous signal transmission. In contrast, the INS system experiences progressive error accumulation, which significantly degrades the positioning accuracy over time. To overcome these challenges, this paper proposes a fusion approach based on a Kalman filter algorithm aimed at combining the strengths of both positioning technologies. Comparative analysis with standalone positioning methods demonstrates that the proposed fusion algorithm significantly enhances accuracy and mitigates error accumulation, thereby validating its effectiveness.