An indoor positioning algorithm for mobile objects based on track smoothing

In this paper, a new indoor positioning algorithm is proposed for mobile objects based on track smoothing. Considering the effects of indoor environment and the individual anchor nodes, the algorithm is realized in two filtering phases to modify the UWB range measurements and the trilateration localization results by the Unscented Kalman Filter, which reduces the influence of the additive non-Gaussian noise. Furthermore, the filtered positioning results of a mobile object are smoothed by a proposed adaptive smoothing algorithm, and the accuracy has been significantly improved with the positioning RMSE less than 0.8m and the maximum error is about 1m.