论文标题
用于事件驱动的室内定位的自我维持的超宽带定位系统
Self-sustaining Ultra-wideband Positioning System for Event-driven Indoor Localization
论文作者
论文摘要
准确跟踪自己位置的智能和不引人注目的移动传感器节点有可能通过基于位置的功能来增强数据收集。为了实现这种不表现的愿景，传感器节点必须具有紧凑的外形效果，并且可以在长时间内运行，而无需电池充电或更换。本文介绍了一个自我维持，准确的基于超宽带的室内定位系统，并带有保守的基础设施开销。事件驱动的传感方法可以平衡在室内条件下收获的有限能量与超宽带收发器的功耗。呈现的中心化概念将异质系统设计与嵌入式处理结合在一起，可以最大程度地减少闲置消耗而无需牺牲功能。尽管需要适度的基础架构，但使用错误校正的双向双向范围和嵌入式最佳多材料，可以实现高定位精度。实验结果证明了该系统的好处：该节点的静止电流为$ 47〜na $，并且在执行能量收集和运动检测的同时以$ 1.2〜μa $的价格运行。位置更新的能源消耗，在现实的非视线条件下的准确度为$ 40〜cm $（2d）为$ 10.84〜MJ $。在资产跟踪案例研究中，在$ 200〜M^2 $多房间的办公空间中，所达到的准确性级别可以识别36个不同的桌子和存储位置，准确性超过$ 95〜 {\％} $。在多个室内照明情况下，已经对系统的长期自我可持续性进行了分析。
Smart and unobtrusive mobile sensor nodes that accurately track their own position have the potential to augment data collection with location-based functions. To attain this vision of unobtrusiveness, the sensor nodes must have a compact form factor and operate over long periods without battery recharging or replacement. This paper presents a self-sustaining and accurate ultra-wideband-based indoor location system with conservative infrastructure overhead. An event-driven sensing approach allows for balancing the limited energy harvested in indoor conditions with the power consumption of ultra-wideband transceivers. The presented tag-centralized concept, which combines heterogeneous system design with embedded processing, minimizes idle consumption without sacrificing functionality. Despite modest infrastructure requirements, high localization accuracy is achieved with error-correcting double-sided two-way ranging and embedded optimal multilateration. Experimental results demonstrate the benefits of the proposed system: the node achieves a quiescent current of $47~nA$ and operates at $1.2~μA$ while performing energy harvesting and motion detection. The energy consumption for position updates, with an accuracy of $40~cm$ (2D) in realistic non-line-of-sight conditions, is $10.84~mJ$. In an asset tracking case study within a $200~m^2$ multi-room office space, the achieved accuracy level allows for identifying 36 different desk and storage locations with an accuracy of over $95~{\%}$. The system`s long-time self-sustainability has been analyzed over $700~days$ in multiple indoor lighting situations.
