Passive indoor localization for mobile Wi-Fi devices, e.g., smartphones, has attracted increasing attention from research communities recently. Existing passive localization techniques leverage received signal strength (RSS) of packets transmitted by target Wi-Fi devices and do not require a dedicated software installed on the devices. However, RSS-based passive localization techniques: 1) are device dependent, which results in poor localization accuracy for a wide variety of mobile devices and 2) cannot perform real-time passive localization. In this article, we present a novel passive localization technique, namely, packet delivery ratio (PDR) fingerprinting, to address these problems. In PDR fingerprinting, the lowest-power and highest-modulation scheme (LPHMS) is proposed to generate device-invariant PDR, which replaces RSS to construct fingerprints, to achieve device-invariant localization accuracy. Moreover, instead of passively monitoring packets rarely sent by mobile devices, in PDR fingerprinting, access points (APs) actively transmit request-to-send (RTS) frames to trigger target devices to reply clear-to-send (CTS) frames to calculate PDR. The RTS/CTS mechanism enables PDR fingerprinting to perform real-time localization. We have conducted extensive experiments in a real-world testbed. The experimental results demonstrate that PDR fingerprinting presents a competitive localization accuracy compared to RSS-based passive fingerprinting methods but is device invariant.

中文翻译：

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数据包传输率指纹识别：实现设备不变的被动室内定位


移动Wi-Fi 设备（例如智能手机）的无源室内定位最近引起了研究界越来越多的关注。现有的被动定位技术利用目标 Wi-Fi 设备传输的数据包的接收信号强度 (RSS)，不需要在设备上安装专用软件。然而，基于RSS的被动定位技术：1）依赖于设备，这导致多种移动设备的定位精度较差；2）无法执行实时被动定位。在本文中，我们提出了一种新颖的被动定位技术，即数据包传输率（PDR）指纹识别，来解决这些问题。在PDR指纹识别中，提出了最低功耗和最高调制方案（LPHMS）来生成设备不变的PDR，代替RSS来构造指纹，以实现设备不变的定位精度。此外，在 PDR 指纹识别中，接入点 (AP) 不是被动地监视移动设备很少发送的数据包，而是主动传输请求发送 (RTS) 帧以触发目标设备回复清除发送 (CTS) 帧来计算PDR。 RTS/CTS机制使PDR指纹能够进行实时定位。我们在现实世界的测试台上进行了广泛的实验。实验结果表明，与基于 RSS 的被动指纹识别方法相比，PDR 指纹识别具有具有竞争力的定位精度，但具有设备不变性。