融合建筑信息模型的基站自标定技术

由于建筑材料的遮挡和吸收，室内的无线信号严重受损，致使全球卫星导航系统在室内场景中效果并不理想，因此基于基站的室内定位技术成为关键，其定位性能与基站标定精度关系密切.基于基站通常布置在建筑体墙面上的事实，提出了一种融合建筑信息模型的基站自标定技术，用于提升自标定性能，同时，使用克拉美罗下界进行理论性能分析.所提技术在半定规划算法中融入了建筑信息模型空间约束.克拉美罗下界分析和算法仿真实验结果表明，融入建筑信息模型中的空间约束有效地提升了基站自标定的精度.

The Beacons Self-Calibration Technology Combined with Building Information Modeling

The global navigation satellite system does not work ideally, because the satellite signal decays rapidly indoors due to the occlusion and absorption of building materials. As a result, the localization technologies based on beacons become state-of-art indoor localization technologies. The accuracy of these localization technologies is tightly related to the beacons' calibration accuracy. Based on the fact that beacons are usually set on the walls, a beacons self-calibration technology based on building information modeling is proposed to improve the performance of self-calibration. In the meantime, Cramer-Rao lower bound (CRLB) is used to analyse its performance in theory. Based on the semidefinite programming self-calibration algorithm, the proposed algorithm considers to use the building information modeling. CRLB analysis and simulation shows the proposed algorithm efficiently improve the accuracy of self-calibration.