Precise localization is one key element of the Internet of Things (IoT). Especially concepts for position estimation when Global Navigation Satellite Systems (GNSS) are unavailable have moved into the focus. One crucial component for localization systems in general and precise runtime-based positioning, in particular, is the necessity of ultra-precise clock synchronization between the receiving base stations. Our work presents a software-based approach for the wireless synchronization of spatially separated base stations using a low-cost off-the-shelf frontend architecture. The proposed system estimates the time synchronization, sampling clock offset, and carrier frequency offset using broadcast signals as Signals of Opportunity. In this paper, we derive the theoretical lower bound for the estimation variance according to the Modified Cramer-Rao Bound. We show that a theoretical time synchronization accuracy in the range of ps and a frequency synchronization precision in the range of milli-Hertz is achievable. An algorithm is presented that estimates the desired parameter based on evaluating the Cross-Correlation Function between base stations. Initial measurements are conducted in a real-world environment. It is shown that the presented estimator nearly reaches the theoretical bound within a time and frequency synchronization accuracy of down to 200 ps and 6 mHz, respectively.

翻译：精确的定位是物联网（IoT）的关键要素之一。当全球导航卫星系统（GNSS）不可用时，位置估计的概念尤其受到关注。对于定位系统，特别是基于精确运行时定位而言，一个关键组成部分是接收基站之间超精密时钟同步的必要性。我们的工作提出了一种基于软件的方法，利用低成本商用前端架构实现空间分离基站的无线同步。所提出的系统使用广播信号作为机会信号，估计时间同步、采样时钟偏移和载波频率偏移。在本文中，我们根据修正的克拉美-罗界推导了估计方差的理论下界。我们证明了理论上可达皮秒（ps）级别的时间同步精度和毫赫兹（mHz）级别的频率同步精度。我们提出了一种基于评估基站间互相关函数的算法来估计所需参数。在真实环境中进行了初步测量。结果表明，所提出的估计器几乎达到了理论界，时间同步精度低至200 ps，频率同步精度低至6 mHz。