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Robust Acoustic Self-Localization of Mobile Devices

机译:移动设备的稳健声学自定位

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Self-localization of smart portable devices serves as foundation for several novel applications. This work proposes a set of algorithms that enable a mobile device to passively determine its position relative to a known reference with centimeter precision, based exclusively on the capture of acoustic signals emitted by controlled sources around it. The proposed techniques tackle typical practical issues such as reverberation, unknown speed of sound, line-of-sight obstruction, clock skew, and the need for asynchronous operation. After their theoretical developments and off-line simulations, the methods are assessed as real-time applications embedded into off-the-shelf mobile devices operating in real scenarios. When line of sight is available, position estimation errors are at most 4 cm using recorded signals.
机译:智能便携式设备的自我定位是一些新颖应用的基础。这项工作提出了一套算法,使移动设备能够完全基于捕获围绕它的受控源发出的声波信号,以厘米为精度被动地确定其相对于已知参考的位置。所提出的技术解决了典型的实际问题,例如混响,未知的声速,视线障碍,时钟偏斜以及异步操作的需求。经过理论发展和离线仿真后,这些方法被评估为嵌入在实际场景中运行的现成移动设备中的实时应用程序。当视线可用时,使用记录的信号,位置估计误差最大为4 cm。

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