Navigating Autonomous Vehicles without Disruptions – A Multi-Sensor System Approach

In the past decade, there has been an unprecedented surge in the adoption of autonomous vehicles (AVs) across diverse sectors, encompassing academia, industry, transportation, aviation, defence, and government agencies. This surge has brought self-driving cars, unmanned ground vehicles (UGVs), and unmanned aerial vehicles (UAVs) into the spotlight. AV technology requires onboard intelligence relying on a suite of sensors and systems such as global navigation satellite systems (GNSS), vehicle motion sensors and remote sensing systems, including cameras, light detection and ranging (LiDAR) and radar. AVs rely heavily on GNSS as the cornerstone for positioning, navigation, and timing (PNT). Ensuring AVs' safe and efficient operation necessitates reliable, accurate, and high-precision positioning across all environmental and operational conditions. Recent years have seen a concerning rise in jamming and spoofing attacks targeting GNSS signals, impacting both military and civilian applications. Furthermore, in urban environments, GNSS signals can be severely obstructed or distorted due to multipath interference. Given the critical safety implications associated with autonomous platforms, there exists an urgent demand for navigation technologies that are resilient and innovative, offering PNT solutions that can either complement or provide complete independence from GNSS. This presentation will discuss the recent research and development towards a comprehensive multisensory system for land vehicle positioning and navigation in urban environments, achieving a decimeter level of positioning accuracy independent of GNSS. The alternative GNSS technologies explored in this work include the LiDAR/Radar perception systems with their capabilities to mimic the surrounding environment and the onboard inertial sensors monitoring the vehicle motion dynamics. This presentation will demonstrate the new land vehicle setup developed at the NavINST research lab and recent results from testing the developed methods in real-time in road test trajectories in Kingston and Ottawa, demonstrating uninterrupted, accurate and high-precision positioning where GNSS cannot work.