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A room-level tag trajectory recognition system based on multi-antenna RFID reader

机译:基于多天线RFID阅读器的房间级标签轨迹识别系统

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摘要

Trajectory of objects is a typical data source of indoor location aware applications and smart systems. In some object tracking applications, the continuity of moving trajectories recognition is more important than its positioning accuracy. To solve the problem of signal coverage blind areas and multi-tag identification reliability, this paper proposes a tag trajectory index method that solves the problem of localized tag trajectories between readers, and establishes a tag identification model based on RFID reader with multiple antennas, which is more economic and efficient in deployment. Furthermore, it proposes a multi-antenna optimization control scheme, which automatically adapts to the actual demands to control the number of working antennas, so as to improve the recognition efficiency. A counterpart indoor tag trajectory reasoning data structure OPTR-tree is proposed, which provides an approach for multi-tag track fast recognition in indoor environment at room-level accuracy. Both theoretical analysis and experimental results show that the proposed multi-antenna model can improve the reliability of multiple tags recognition inside buildings Hopefully, the indoor trajectories data can offer a new way for more effective disaster management.
机译:对象的轨迹是室内位置感知应用程序和智能系统的典型数据源。在某些对象跟踪应用中,运动轨迹识别的连续性比其定位精度更为重要。为解决信号覆盖盲区和多标签识别可靠性的问题,提出了一种标签轨迹索引方法,解决了阅读器之间标签轨迹局部化的问题,建立了基于多天线RFID阅读器的标签识别模型。部署起来更加经济高效。此外,提出了一种多天线优化控制方案,该方案可以自动适应实际需求来控制工作天线的数量,从而提高识别效率。提出了一种对应的室内标签轨迹推理数据结构OPTR-tree,它为室内环境下的室内水平多标签轨迹快速识别提供了一种方法。理论分析和实验结果均表明,所提出的多天线模型可以提高建筑物内部多个标签识别的可靠性。希望室内轨迹数据可以为更有效的灾害管理提供一种新途径。

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