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GNSS technology has had a reputation for unreliability in safety-critical applications, such as advanced driver assistance systems (ADAS). This perception has shaped automotive design and manufacturing: some ADAS developers have avoided GNSS altogether, instead relying on cameras, lidar and other sensors. Here, Manuel Del Castillo, VP of business development at Focal Point Positioning, explains how, with the right reliability, GNSS can offer a powerful layer of redundancy and support these other sensor types.
The hesitation to include GNSS in ADAS stacks is historical. Traditionally, this technology was unreliable, especially in dense, urban environments where satellite signals were obstructed. Consequently, many automakers turned to alternative sensors. For example, cameras can identify lane markings, traffic signs and objects, while lidar can build highly detailed 3D maps of the vehicle’s surroundings.
Each of these sensors provides important navigational data. However, they all describe a car’s location relative to its immediate environment. With no reliable source of absolute positioning, these relative measurements can’t confirm the vehicle’s exact place in the world — information that is critical for safe navigation.
Why ADAS Needs GNSS
Cameras, lidar and other sensors provide rich environmental data. However, they are limited by what they can directly observe. A camera can identify lane markings but can’t confirm which road the vehicle is on when multiple lanes or junctions overlap. Similarly, lidar can map obstacles in 3D, but without a wider frame of reference, it will struggle to anchor that map to the road network. HD maps provide another valuable layer, but without an accurate global position, they too can be misaligned with the real world, limiting their value.
GNSS can help plug this gap. By supplying absolute latitude and longitude, it ensures that the relative information from the other sensors is grounded in the correct location. GNSS helps calibrate and initialise other sensors, while also providing a cross-check against their measurements to detect potential errors or drift in sensor performance over time. Therefore, reliable GNSS is not an alternative to cameras, lidar or radar. It complements these sensors and boosts accuracy and the reliability of the overall system.
The Importance of Redundancy
Increasingly, the importance of GNSS in ADAS stacks is being recognised. As automotive production moves toward L3 automation and beyond, the demand for absolute positioning increases, along with the need for safe, layered sensing. GNSS, alongside cameras, lidar and radar, can help automakers improve navigational resilience without reinventing vehicular architectures.
Reliable GNSS isn’t about replacing other technologies. It is about reinforcing them. Having a global frame of reference helps ensure that the relative data from other sensors is grounded in the correct place. For automakers, the next step is recognising that GNSS can improve safety and trust in ADAS stacks, supporting the transition toward autonomous driving.
Advancing GNSS Reliability
Even with GNSS integrated into the vehicle’s sensors, challenges remain. Urban canyons and dense foliage can attenuate or even block satellite signals and create reflections, reducing accuracy. Since ADAS systems need reliably accurate absolute positioning, these challenges need to be addressed if we want GNSS to play a role in ADAS.
Newer, more sophisticated GNSS solutions are needed. The progression to Level 3 does not require an entirely new technology stack but rather extracting the very best from each of the existing components. For GNSS, this evolution involves implementing software-based solutions to achieve the necessary reliability improvements without overhauling hardware components. Pursuing cost-effective upgrades enhances performance without necessitating complete system redesigns, thereby keeping costs under control.
FocalPoint’s S-GNSS Auto software enhances GNSS accuracy in autonomous vehicles, providing reliable, absolute location to improve overall ADAS safety and efficiency. By boosting line-of-sight signals and rejecting non-line-of-sight signals, this simple firmware upgrade can help vehicles maintain accuracy in challenging environments.
By reducing positional uncertainty, these enhanced GNSS solutions strengthen the overall sensor stack. Together, these layers improve resilience, safety, and confidence in higher levels of vehicle automation.
As the automotive industry moves further towards L3 automation and beyond, reliable data on absolute position will be essential and will only reinforce the insights captured by cameras, lidar and other sensors.
To find out how S-GNSS Auto can help automotive OEMs transition to L3 autonomy, download FocalPoint’s white paper here.
