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Given that the challenges inherent in complex indoor environments where GPS signals are often weak, various alternative signals have been employed for indoor positioning. Ultra-wideband (UWB) technology, distinguished by its high-precision positioning capability, has an extensive application in fields of indoor positioning. Nevertheless, it is susceptible to the effects of multi-path propagation and non-line-of-sight (NLOS) conditions, which can introduce significant inaccuracies into positioning outcomes. To improve the accuracy and stability of positioning in complex indoor environments, this study presents a dynamic feasible region-based particle filter (DFRPF). It effectively solves the issues of particle convergence and weak robustness to NLOS. Moreover, the observation likelihood function undergoes dynamic adjustment based on the received UWB signal power quality, thereby enhancing the system's adaptability to diverse environments. Numerical experiments in different scenarios show that the proposed fusion approach can maintain high levels of accuracy and stability in complex indoor environments.
Liu et al. (Wed,) studied this question.