# GNSS Performance Modelling and Augmentation for Urban Air Mobility +
## 1 Introduction  
Several Location-Based Services (LBS) for personal navigation and Intelligent Transport Systems (ITS) are subject to the availability of robust positioning, navigation and timing measurements. The Global Navigation Satellite Systems (GNSS) provides a positioning solution that is free of drift as opposed to dead-reckoning systems such as the Inertial Navigation System (INS) [1; 2]. However, due to a dependency on unobstructed line of sight between the mobile receiver antenna and the orbiting satellites, several advantages offered by GNSS are removed in dense urban environments. These environments are characterized by severe signal multipath and a high Dilution Of Precision due to unfavourable satellite geometry [3]. Rigorous navigation performance analysis is crucial for the safe operation of Unmanned Aircraft Systems (UAS). Roadmaps in different countries are aimed at the gradual introduction of UAS in previously restricted airspace including dense urban areas. Urban Air Mobility (UAM) is an emerging term encompassing not only UAS operations but also future on-demand urban air transportation (the so-called 'air-taxi'). This emerging use-case is still in a conceptual stage at the time of writing. The efforts of most manufacturers in this domain are aimed at Distributed Electric Propulsion (DEP), Vertical Take-Off and Landing (VTOL) capability, and progressive automation of several safety-critical and mission-specific functions. Initial offerings include (Figure 1) aerial logistics platforms such as the Skyways, and passenger aircraft such as the Airbus Vahana, Pop.up and the Volocopter. Initial feasibility studies [4] have beenconducted that identify the key system requirements to be met for a pathway to market. Given the projected population of civilian UAS and UAM platforms [5], progressive introduction of autonomy is required for several functions such as monitoring trajectory conformance, envelope protection, and sensor performance to achieve feasibility from the perspective of pilot workload. Under this new paradigm, several locations in urban environments could emerge as favourable nodes for UAS and UAM platforms. This places capacity and safety requirements on low-level (below 500 feet) urban airspace. Conceptual airspace structures to accommodate these new users are currently being proposed under the UAS Traffic Management (UTM) framework, the European U-space and similar initiatives around the globe. Figure 2 illustrates the Technical Capability Levels (TCL) of the UTM undertaking. A successive progression from Visual Line Of Sight (VLOS) operations in scarcely populated areas to Beyond Visual Line Of Sight (BVLOS) operations in urban areas can be observed, highlighting the need for robust Communication, Navigation and Surveillance (CNS) systems. Figure 1: VTOL platform prototypes and concepts for Urban Air Mobility (**a**) Airbus Vahana (**b**) Airbus Pop.up (**c**) Volocopter (**d**) Airbus Skyways. Figure 2: Phases of the UTM project. Novel airspace structuring concepts are emerging in response to the drive to introduce UAM and UAS operations in urban environments. These include stacked layers [6], dynamic 4D tubes, designated zones [7], and urban air corridors. Urban Airspace access is likely to be based on aircraft capabilities including accurate, precise and reliable trajectory tracking and conformance, and robust Detect and Avoid (DAA) systems. These functions are highly dependent on the performance of the onboard navigation system. Navigation errors and uncertainties, in the first instance, lower the remote pilots' situational awareness, and within a shared information network, ultimately propagate to cooperative surveillance systems, thereby lowering Separation Assurance and DAA capability. Therefore, persistent and high-performance navigation, and performance prediction are prerequisites for the implementation of a safe UAM framework. Most UAS navigation systems in the civilian market rely primarily on GNSS as the sole source of absolute positioning.