Scanning and Detection of LTE Radio Signals with Applications to Traffic Monitoring Systems

空间和时间行人运动数据（即按时间、星期和季节计算的行人暴露量）对于许多应用程序都很重要，对政府机构和城市规划者很有用。这些应用需要一个有效的行人交通监控系统。然而，目前最先进的行人交通监测技术在无约束和不可预测的步行路径上的行人交通时空分析方面存在局限性。射频扫描是一种新兴的行人交通监测技术，例如对移动电话发出的无线电信号进行扫描，它可以克服现有技术的许多局限性。在这个项目中，我的研究小组将开发一个基于LTE/LTE- advanced手机扫描无线电信号的行人交通监控系统的硬件原型。该系统将被MORR交通咨询有限公司（MORR）使用，这是一家总部位于温尼伯的交通咨询公司，用于开发一种可扩展的行人监控技术产品，并将在加拿大各地部署。MORR是该项目的行业合作伙伴，拥有土木工程和计算机科学研究经验，可以为这项技术开发软件组件。然而，MORR缺乏研究专业知识来开发用于嗅探该技术中使用的LTE无线电信号的硬件原型。在MORR的指导下，开发的硬件原型的能力将被评估并与一些基线系统进行比较。我的研究团队还将研究基于行人运动数据识别行人交通轨迹的算法开发。

Spatial and temporal pedestrian movement data (i.e., pedestrian exposure in terms of volumes by time-of-day, day-of-week, and season) are important for numerous applications which are useful for government agencies and city planners. An effective pedestrian traffic monitoring system is required for these applications. However, the state-of-the-art pedestrian traffic monitoring technologies have limitations for spatio-temporal analysis of pedestrian traffic traveling along unconfined and unpredictable travel paths. Radio frequency scanning, for example, scanning of radio signals emitted by mobile phones is an emerging technique for pedestrian traffic monitoring which can overcome many limitations of the existing technologies. In this project, my research team will develop a hardware prototype for pedestrian traffic monitoring system based on scanning radio signals from LTE/LTE-Advanced phones. This system will be used by MORR Transportation Consulting Ltd. (MORR), which is a Winnipeg-based transportation consulting company, to develop a scalable product for the pedestrian monitoring technology to be deployed across Canada. MORR, the industry partner for this project, has the civil engineering and computer science research experience to develop the software components for this technology. However, MORR lacks the research expertise to develop this hardware prototype for sniffing LTE radio signals to be exploited in this technology. With the guidance from the MORR, the capability of the developed hardware prototype will be assessed and compared against some baseline systems. My research team will also investigate the development of algorithms to discern trajectory of pedestrian traffic based on the pedestrian movement data.