当前位置: X-MOL 学术Neural Comput. & Applic. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Map-aided and UWB-based anchor placement method in indoor localization
Neural Computing and Applications ( IF 6 ) Pub Date : 2021-03-17 , DOI: 10.1007/s00521-021-05851-9
Hao Pan , Xiaogang Qi , Meili Liu , Lifang Liu

Nowadays, ultra wideband (UWB) has been popular in indoor positioning systems. Because of obstacles such as walls, doors, desks and pedestrians in the indoor area, UWB devices have to be conducted in a non-line-of-sight (NLOS) environment. The placement of nodes has significant influences on the performance of localization. In this paper, an anchor placement method for the target’s trajectory based on genetic heuristic differential evolution algorithm is proposed to improve the UWB localization accuracy. To be specific, in an area with low anchor densities, a target does not have enough anchors for multilateration localization; thus, a coverage degree criterion is defined. Meanwhile, the Cramer–Rao lower bound (CRLB) is used as an evaluation metric for localization accuracy, and both of CRLB and coverage degree criterion are incorporated into the evaluation function of the differential evolution (DE) algorithm. Furthermore, instead of using the liner distance path loss model, the more practical UWB-based through-wall signal propagation model is adopted to reflect the influences of obstacles that are widespread in indoor environments. In addition, a software application is developed to visualize the indoor scenario, signal propagation status and anchor placement results. Finally, field experiments and simulations are performed, and a thorough case study confirms the effectiveness of the proposed method. The average localization error of the proposed placement scheme can be reduced by 28.2% and 12.5% compared to the random scheme and the default DE-based scheme.



中文翻译:

室内定位中基于地图和基于UWB的锚点放置方法

如今,超宽带(UWB)已在室内定位系统中流行。由于室内区域的墙壁,门,书桌和行人等障碍,UWB设备必须在非视线(NLOS)环境中进行操作。节点的位置对定位性能有重要影响。提出了一种基于遗传启发式差分进化算法的目标轨迹锚点定位方法,以提高UWB定位精度。具体来说,在锚点密度低的区域,目标没有足够的锚点进行多边定位。因此,定义了覆盖度标准。同时,将Cramer-Rao下界(CRLB)用作评估定位精度的指标,并且将CRLB和覆盖度标准都纳入了差分演化(DE)算法的评估功能中。此外,代替使用直线距离路径损耗模型,而是采用更实用的基于UWB的穿墙信号传播模型来反映在室内环境中普遍存在的障碍物的影响。另外,开发了软件应用程序以可视化室内场景,信号传播状态和锚点放置结果。最后,进行了现场实验和模拟,并进行了详尽的案例研究,证实了所提方法的有效性。与随机方案和默认的基于DE的方案相比,所提出的布局方案的平均定位误差可以降低28.2%和12.5%。

更新日期:2021-03-17
down
wechat
bug