In indoor localization systems, improving the accuracy of indoor localization can be achieved by optimizing existing localization algorithms. This paper first utilizes Ultra-Wideband (UWB) technology and an improved Time-of-Flight (TOF) algorithm to obtain high-precision distance information, thereby enhancing ranging accuracy. Subsequently, the Chan algorithm is employed to obtain the initial three-dimensional coordinates, which are then optimized using both the Taylor series expansion and an improved Unscented Kalman Filter (UKF) algorithm, resulting in two optimized coordinates. Finally, the two optimized coordinates are integrated through weighted fusion to obtain the final localization result. Experimental results demonstrate that the proposed algorithm improves indoor localization accuracy by over 60%, significantly enhancing the precision of indoor localization.
Ma et al. (Tue,) studied this question.