Robust Localization for Mobile Targets Along a Narrow Path With LoS/NLoS Interference

Deterministic Localization for Fully Automatic Operation: A Survey and Experiments

“…Compared with other localization technologies, it has certain advantages in terms of accuracy in both outdoor and indoor scenarios. However, NLoS propagation has a significant impact on its localization accuracy, and localization in circumscribed regions, such as narrow spaces, is particularly challenging [19,42]. Regarding localization with NLoS propagations, most detected interferences and discarded outliers, where ranging results were not fully utilized.…”

“…In [43], a Schmidt KF was used to compensate the bias caused by NLoS propagation, instead of discarding. Considering mixed LoS/NLoS scenarios, a joint LoS/NLoS interference detection and mitigation algorithm was proposed in [19], which reduced the dynamic interference to some extent. Besides, the deployment strategies of UWB anchors are also particularly important to the localization performance and robustness.…”

“…As a result, the ranging results of UWB anchors in front of the train can only be utilized to solve the train's location. From our previous work [19], we can calculate the localization error at a given position x, expressed as MSE(A, x) = (Aφ) T Aφ (9) where the vector φ can be solved in [19]. The localization MSE is related to the tag's location and anchor deployment, which can determine the matrix A.…”

“…Since UWB anchors and the tag are mounted on the metal mesh and the train, respectively, there are strong metal interferences during localization. As presented in our previous work [19], we firstly constructed the model of the interference model. Secondly, the ranging error of each propagation path was iteratively updated and corrected.…”

“…However, during the wireless propagation and position solution, the anchor deployment and non-line-of-sight (NLoS) propagations have a significant impact on its localization performance [15,16]. As a result, some relevant researches aim to minimize the average localization root mean square error (RMSE) by anchor deployment optimization [17,18] or NLoS interference mitigation [19,20].…”