Intelligent Positioning in Cities using GNSS and Enhanced 3D Mapping

在人口稠密的市区，定位性能差是实际实现新技术的主要障碍，这些新技术包括为视障人士提供导航、跟踪患有慢性病的人、增强现实、先进的车辆车道控制系统和先进的铁路信号系统。全球定位系统(GPS)在开放环境中提供米级别的定位。然而，在人口密集的城市地区，建筑物会阻挡、衰减、反射和绕射无线电信号，当接收到足够的信号来计算位置时，实时定位精度限制在10-50米。其他无线电定位技术通常不会更准确，而通过航位推算获得的位置会随着时间的推移而退化。机器人界开发的光学技术比其他应用更适合某些应用，目前仍在进行研究，以使其更可靠和更高效。除GPS外，使用新的全球导航卫星系统(GNSS)星座(即GLONASS和未来的伽利略和罗盘)可以改善城市地区基于卫星的定位的可用性。然而，为了提高精度，需要一种新的定位方法，而3D地图的日益普及为实现这一目标提供了机会。因此，该项目的目的是通过将多星座全球导航卫星系统与3D制图相结合，将城市地区实时移动定位的精度提高到几米以内，这一概念被称为智能城市定位。通过利用3D城市模型提供的环境知识，并自下而上地重建定位算法，利用所有可用信息，定位性能可以实现阶梯式变化，释放出大量新定位应用的潜力。这项研究将基于伦敦大学学院在城市定位方面的创新记录，包括开发一种全新的GNSS定位方法，称为阴影匹配。该项目将研究使用3D映射来辅助基于测距的GNSS定位的新方法，然后将其与阴影匹配相结合，以获得最佳的整体位置解决方案。将在广泛的情景下进行测试，以评估性能如何随城市环境、所使用的全球导航卫星系统用户设备的类别以及3D测绘的特点而变化。最后，将开发上下文检测算法，以确定定位系统何时处于适合该项目开发的算法的环境中，以及何时处于应该部署常规GNSS算法或室内定位技术的环境中。通过提高城市定位的准确性和可靠性，该项目的成功结果将释放许多新应用的潜力，这些应用既能为经济做出贡献，又能为社会问题提供解决方案，同时还能提高许多现有技术的可靠性。定位技术可以确定街道的正确一侧，并识别邻近的建筑物，是视障行人自动导航的关键组成部分。更准确的紧急呼叫者位置和对慢性病患者的跟踪使响应团队能够更快地到达。增强现实将受益于更高效地覆盖周围环境的信息。研究人员绘制了城市空气污染或轮椅无障碍模式的地图，将能够快速而廉价地将信息定位到几米以内。更可靠的车道和铁轨识别将支持先进智能交通系统的发展。为前往城市的游客提供路线指南，在复杂或拥挤的城市环境中为朋友和商业伙伴定位，以及基于位置的广告也将受益。

Poor positioning performance in dense urban areas is a major obstacle to the practical realisation of new technologies such as navigation for the visually impaired, tracking people with chronic medical conditions, augmented reality, advanced lane control systems for vehicles and advanced railway signalling systems.The Global Positioning System (GPS) provides metres-level positioning in open environments. However in dense urban areas, buildings block, attenuate, reflect and diffract radio signals, limiting the real-time positioning accuracy to 10-50m when enough signals can be received to calculate a position. Other radio positioning technologies are typically no more accurate, while position obtained from dead reckoning degrades with time. Optical techniques developed by the robotics community are more suited to some applications than others and are still undergoing research to make them more reliable and efficient.Using the new global navigation satellite systems (GNSS) constellations (i.e., GLONASS and, in future, Galileo and Compass) in addition to GPS improves the availability of satellite-based positioning in urban areas. However, to improve the accuracy, a new approach to positioning is needed and the increasing availability of 3D mapping provides an opportunity to achieve this. The aim of this project is thus to improve the accuracy of real-time mobile positioning in urban areas to within a few metres by combining multi-constellation GNSS with 3D mapping, a concept known as intelligent urban positioning. By exploiting knowledge of the surroundings provided by 3D city models and rebuilding the positioning algorithms from the bottom up to make use of all available information, a step change in positioning performance can be achieved, unlocking the potential for a host of new positioning applications.This research will build on UCL's track record of innovation in urban positioning, including the development of a brand new GNSS positioning method known as shadow matching. This project will investigate new ways of using 3D mapping to aid ranging-based GNSS positioning and then combine this with shadow matching to obtain the best overall position solution. Testing will be conducted under a wide range of scenarios to assess how the performance varies as a function of the urban environment, the class of GNSS user equipment used and the characteristics of the 3D mapping. Finally, context detection algorithms will be developed to determine when the positioning system is in an environment suitable for the algorithms developed under this project and when it is in an environment where conventional GNSS algorithms or an indoor positioning technique should be deployed instead.By improving the accuracy and reliability of urban positioning, a successful outcome of this project would unlock the potential for many new applications that can both contribute to the economy and provide solutions to societal problems, while improving the reliability of many existing technologies. Positioning technology that can determine the correct side of the street and identify adjacent buildings is a key component of automated guidance for visually impaired pedestrians. More accurate emergency caller location and tracking of people with chronic medical conditions enables response teams to arrive more quickly. Augmented reality will benefit from a more efficient overlaying of information on the surrounding environment. Researchers mapping patterns of air pollution or wheelchair accessibility in cities will be able to quickly and cheaply geolocate information to within a few metres. More reliable identification of traffic lanes and railway tracks will support the development of advanced intelligent transport systems. Route guidance for visitors to cities, location of friends and business associates in complex or crowded urban environments, and location-based advertising will also benefit.