The potential of multi-sensor fusion for indoor positioning has attracted substantial attention. A ZUPT/UWB data fusion algorithm based on graph optimization is proposed in this paper and is compared with the traditional fusion algorithms, which are based on particle filtering. With a series of observations, the proposed algorithm can achieve higher precision with acceptable computational complexity. Two methods for dynamically determining the confidence level are also presented. The first method can reduce the confidence level of ZUPT at corners, and the second method can determine the lower bound on the UWB sensor’s confidence level through the UWB optimized residual. Experimental results demonstrate the ability of the proposed method to achieve a positioning accuracy of 0.4 m, which is better than the 0.7 m achieved by the particle-filtering-based fusion method.
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