Chinese Academy of Surveying and Mapping, Beijing 100036, China.
School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China.
Sensors (Basel). 2022 Dec 8;22(24):9634. doi: 10.3390/s22249634.
As an indispensable type of information, location data are used in various industries. Ultrawideband (UWB) technology has been used for indoor location estimation due to its excellent ranging performance. However, the accuracy of the location estimation results is heavily affected by the deployment of base stations; in particular, the base station deployment space is limited in certain scenarios. In underground mines, base stations must be placed on the roof to ensure signal coverage, which is almost coplanar in nature. Existing indoor positioning solutions suffer from both difficulties in the correct convergence of results and poor positioning accuracy under coplanar base-station conditions. To correctly estimate position in coplanar base-station scenarios, this paper proposes a novel iterative method. Based on the Newton iteration method, a selection range for the initial value and iterative convergence control conditions were derived to improve the convergence performance of the algorithm. In this paper, we mathematically analyze the impact of the localization solution for coplanar base stations and derive the expression for the localization accuracy performance. The proposed method demonstrated a positioning accuracy of 5 cm in the experimental campaign for the comparative analysis, with the multi-epoch observation results being stable within 10 cm. Furthermore, it was found that, when base stations are coplanar, the test point accuracy can be improved by an average of 63.54% compared to the conventional positioning algorithm. In the base-station coplanar deployment scenario, the upper bound of the CDF convergence in the proposed method outperformed the conventional positioning algorithm by about 30%.
作为一种不可或缺的信息类型，位置数据被广泛应用于各个行业。超宽带 (UWB) 技术由于其出色的测距性能，被用于室内定位估计。然而，位置估计结果的准确性受到基站部署的严重影响；特别是在某些场景下，基站的部署空间有限。在地下矿山中，基站必须安装在屋顶上以确保信号覆盖，这几乎是共面的。现有的室内定位解决方案在共面基站条件下存在结果正确收敛和定位精度差的困难。为了在共面基站场景中正确估计位置，本文提出了一种新颖的迭代方法。基于牛顿迭代法，推导出初始值的选择范围和迭代收敛控制条件，以提高算法的收敛性能。本文从数学上分析了共面基站定位解的影响，并推导出定位精度性能的表达式。在比较分析的实验中，所提出的方法的定位精度达到了 5 厘米，多历元观测结果稳定在 10 厘米以内。此外，研究发现，当基站共面时，与传统定位算法相比，测试点的精度可以提高平均 63.54%。在基站共面部署场景中，所提出方法的 CDF 收敛上限比传统定位算法高出约 30%。
