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    基于智能手机声信号的自标定室内定位系统

    Acoustic Self-Calibrating Indoor Localization System via Smartphones

    • 摘要: 随着室内位置信息服务需求的爆发式增长,对室内定位系统的定位精度、与智能手机的兼容性、成本控制、实时性及数据更新速率等提出了新的要求.基于通用智能手机平台,应用声技术提出了一种新的锚节点自标定与用户定位方法,设计并实现了一套室内定位系统:LinLoc.该系统在声技术TPSN测距模型的基础上,利用到达时间(time of arrival, TOA)估计技术,提出一种高实时性的用户定位方法,实现了厘米级别的用户定位,无需时间同步且与智能手机完全兼容,同时提出一种基于TPSN测距的半定规划(semidefinite programming, SDP)锚节点自标定方法,解决了大规模网络中锚节点的坐标标定及后期维护问题.针对LinLoc系统做了充分的仿真及实验,其结果表明:系统性能良好,定位精度可达0.05~0.3m,能够在室内环境中为人们提供精确的位置信息服务.

       

      Abstract: Growing needs for the indoor location based service (ILBS) bring newer and higher requirements for indoor localization systems, such as high accuracy, hardware compatibility, low cost for commercial application, instantaneity and fast data update rate etc. In order to meet those requirements with commercial smartphone platform, we design an indoor localization system named LinLoc, which includes a new self-calibrating approach and a new localization method. Based on TPSN ranging, LinLoc applies time-of-arrival (TOA) method with acoustic signals to achieve real-time users' localization on normal commercial smartphone platform. With no extra time synchronization need, it can achieve centimeter-level accuracy. Furthermore, we propose a new self-calibrating approach based on acoustic TPSN ranging and semidefinite programming (SDP) algorithm. Through the interaction of every anchor nodes in the network, the new approach helps to solve the problem of self-calibrating in large-scale anchor network, and also helps to remove the heavy maintenance requirements afterwards. Then, LinLoc system which consists of a special-designed anchor network, smartphones installed with real-time app inside, and a backend server for processing is implemented. Simulations and experiments have been performed. The results show that LinLoc has nice indoor localization performance and its accuracy can be 0.05~0.3m, which provides accurate ILBS for users.

       

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