Satellite Navigation for the Age of Autonomy

Global Navigation Satellite Systems (GNSS) brought navigation to the masses. Coupled with smartphones, the blue dot in the palm of our hands has forever changed the way we interact with the world. Looking forward, cyber-physical systems such as self-driving cars and aerial mobility are pushing the limits of what localization technologies including GNSS can provide. This autonomous revolution requires a solution that supports safety-critical operation, centimeter positioning, and cyber-security for millions of users. To meet these demands, we propose a navigation service from Low Earth Orbiting (LEO) satellites which deliver precision in-part through faster motion, higher power signals for added robustness to interference, constellation autonomous integrity monitoring for integrity, and encryption / authentication for resistance to spoofing attacks. This paradigm is enabled by the 'New Space' movement, where highly capable satellites and components are now built on assembly lines and launch costs have decreased by more than tenfold. Such a ubiquitous positioning service enables a consistent and secure standard where trustworthy information can be validated and shared, extending the electronic horizon from sensor line of sight to an entire city. This enables the situational awareness needed for true safe operation to support autonomy at scale.Comment: 11 pages, 8 figures, 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS

SaPPART White paper. Better use of Global Navigation Satellite Systems for safer and greener transport

Transport and mobility services are crucial to the society that faces important challenges. Up to date, transport facilities and services have been fundamental to economic growth. However, there have significant and unacceptable negative impacts on the environment including pollution, noise and climate change. Therefore, it is paramount that the efficiency of the transport system is improved significantly including lower consumption of energy. A way of achieving this is through the concept of smart transport that exploits Intelligent Transport Systems (ITS) technology. ITS are built on three technology pillars: information, communication and positioning technologies. Of the three technologies, positioning could be argued to be the least familiar amongst transport stakeholders. However, a quick investigation reveals that there are a wide variety of transport and related services often associated with communication technologies that are supported by positioning. Currently, the positioning is provided in the majority of the cases by Global Navigation Satellite System (GNSS), among which the Global Positioning System (GPS) is the pioneer and still the most widely used system. The other current fully operational stand-alone system is Russia’s GLONASS. As these operational systems were not originally and specifically designed for transport applications, the actual capabilities and limitations of the current GNSS are not fully understood by many stakeholders. Therefore, better knowledge of these limitations and their resolution should enable a much more rapid deployment of ITS. This white paper is produced by the members of the COST Action SaPPART with two principal aims. The first is to explain the principles, state-of-the-art performance of GNSS technology and added value in the field of transport. The second aim is to deliver key messages to the stakeholders to facilitate the deployment of GNSS technology and thus contribute to the development of smarter and greener transport systems. The first chapter highlights the important role of positioning in today transport systems and the added value of accurate and reliable positioning for critical systems. The second chapter is about positioning technologies for transport: GNSS and their different aiding and augmentation methods are described, but the other complementary technologies are also introduced. The third and last chapter is about the management of performances inside a positioning-based intelligent transport system, between the positioning system itself and the application-specific part of the system which processes the raw position for delivering its service

Collaborative navigation as a solution for PNT applications in GNSS challenged environments: report on field trials of a joint FIG / IAG working group

PNT stands for Positioning, Navigation, and Timing. Space-based PNT refers to the capabilities enabled by GNSS, and enhanced by Ground and Space-based Augmentation Systems (GBAS and SBAS), which provide position, velocity, and timing information to an unlimited number of users around the world, allowing every user to operate in the same reference system and timing standard. Such information has become increasingly critical to the security, safety, prosperity, and overall qualityof-life of many citizens. As a result, space-based PNT is now widely recognized as an essential element of the global information infrastructure. This paper discusses the importance of the availability and continuity of PNT information, whose application, scope and significance have exploded in the past 10–15 years. A paradigm shift in the navigation solution has been observed in recent years. It has been manifested by an evolution from traditional single sensor-based solutions, to multiple sensor-based solutions and ultimately to collaborative navigation and layered sensing, using non-traditional sensors and techniques – so called signals of opportunity. A joint working group under the auspices of the International Federation of Surveyors (FIG) and the International Association of Geodesy (IAG), entitled ‘Ubiquitous Positioning Systems’ investigated the use of Collaborative Positioning (CP) through several field trials over the past four years. In this paper, the concept of CP is discussed in detail and selected results of these experiments are presented. It is demonstrated here, that CP is a viable solution if a ‘network’ or ‘neighbourhood’ of users is to be positioned / navigated together, as it increases the accuracy, integrity, availability, and continuity of the PNT information for all users

Hazard alerting and situational awareness in advanced air transport cockpits

Advances in avionics and display technology have significantly changed the cockpit environment in current 'glass cockpit' aircraft. Recent developments in display technology, on-board processing, data storage, and datalinked communications are likely to further alter the environment in second and third generation 'glass cockpit' aircraft. The interaction of advanced cockpit technology with human cognitive performance has been a major area of activity within the MIT Aeronautical Systems Laboratory. This paper presents an overview of the MIT Advanced Cockpit Simulation Facility. Several recent research projects are briefly reviewed and the most important results are summarized

All Source Sensor Integration Using an Extended Kalman Filter

The global positioning system (GPS) has become an ubiquitous source for navigation in the modern age, especially since the removal of selective availability at the beginning of this century. The utility of the GPS is unmatched, however GPS is not available in all environments. Heavy reliance on GPS for navigation makes the warfighter increasingly vulnerability as modern warfare continues to evolve. This research provides a method for incorporating measurements from a massive variety of sensors to mitigate GPS dependence. The result is the integration of sensor sets that encompass those examined in recent literature as well as some custom navigation devices. A full-state extended Kalman filter is developed and implemented, accommodating the requirements of the varied sensor sets and scenarios. Some 19 types of sensors are used in multiple quantities including inertial measurement units, single cameras and stereo pairs, 2D and 3D laser scanners, altimeters, 3-axis magnetometers, heading sensors, inclinometers, a stop sign sensor, an odometer, a step sensor, a ranging device, a signal of opportunity sensor, global navigation satellite system sensors, an air data computer, and radio frequency identification devices. Simulation data for all sensors was generated to test filter performance. Additionally, real data was collected and processed from an aircraft, ground vehicles, and a pedestrian. Measurement equations are developed to relate sensor measurements to the navigation states. Each sensor measurement is incorporated into the filter using the Kalman filter measurement update equations. Measurement types are segregated based on whether they observe instantaneous or accumulated state information. Accumulated state measurements are incorporated using delayed-state update equations. All other measurements are incorporated using the numerically robust UD update equations

Infrastructure Wi-Fi for connected autonomous vehicle positioning : a review of the state-of-the-art

In order to realize intelligent vehicular transport networks and self driving cars, connected autonomous vehicles (CAVs) are required to be able to estimate their position to the nearest centimeter. Traditional positioning in CAVs is realized by using a global navigation satellite system (GNSS) such as global positioning system (GPS) or by fusing weighted location parameters from a GNSS with an inertial navigation systems (INSs). In urban environments where Wi-Fi coverage is ubiquitous and GNSS signals experience signal blockage, multipath or non line-of-sight (NLOS) propagation, enterprise or carrier-grade Wi-Fi networks can be opportunistically used for localization or “fused” with GNSS to improve the localization accuracy and precision. While GNSS-free localization systems are in the literature, a survey of vehicle localization from the perspective of a Wi-Fi anchor/infrastructure is limited. Consequently, this review seeks to investigate recent technological advances relating to positioning techniques between an ego vehicle and a vehicular network infrastructure. Also discussed in this paper is an analysis of the location accuracy, complexity and applicability of surveyed literature with respect to intelligent transportation system requirements for CAVs. It is envisaged that hybrid vehicular localization systems will enable pervasive localization services for CAVs as they travel through urban canyons, dense foliage or multi-story car parks