In an exclusive interview first published in the September 2026 issue of ADAS & Autonomous Vehicle International magazine, Steve Mole, VP of engineering at Focal Point Positioning, explains how Precise+ delivers high-precision GNSS in even the toughest environments. (Subscribe to receive future issues of the magazine, for free, by clicking here.)
What is high-precision positioning and what are its limitations?
Standard GNSS uses the digital ranging signals that GNSS satellites transmit to calculate an absolute position in the world. It is used every day in car map displays, cell phones, watches, etc. The accuracy of standard GNSS is limited to about 2m in open-sky environments most of the time. It is degraded in environments where GNSS signals are obstructed; for example, in cities where buildings block the signals, or in forests where trees and leaves obstruct the signal. In these environments, the accuracy is worse than 2m, dropping to 10m, 50m or beyond, depending on the environment and other factors.
Instead of the digital signal, high-precision GNSS uses the GNSS carrier signal. High-precision GNSS navigation engines also require additional data from satellites or the internet but the accuracy in open-sky environments can be much improved over standard GNSS – 10cm or better. However, in the same difficult environments that limit the accuracy of standard GNSS, the accuracy of high-precision GNSS degrades sharply, often to the same level as standard GNSS. That is, even though high-precision GNSS is more accurate than standard GNSS in open-sky environments, it is often no more accurate than standard GNSS in cities or under foliage. This is frustrating for system designers and end users who pay extra for high-precision GNSS but see little or no benefit in some environments.
What is Precise+ and how does it differ from S-GNSS Auto, your current product?
S-GNSS Auto is built on our patented Supercorrelation technology and improves code phase and frequency measurements – critical for standard and high-precision positioning. S-GNSS already mitigates the effect of signal obstruction for GNSS receivers and has been demonstrated worldwide. Essentially, in environments where standard GNSS accuracy would degrade, S-GNSS limits or eradicates the degradation so the GNSS accuracy is closer to the ideal, open-sky accuracy.
By accurately modeling the local time standard and the motion of the GNSS antenna through space, S-GNSS enables long, coherent integration and – fundamentally – introduces angular sensitivity to the GNSS receiver. Mass-market GNSS devices with single-node GNSS antennas simply receive all the GNSS signal energy that enters the antenna gain pattern. S-GNSS effectively allows the gain pattern to be dynamically modified in software to attenuate signals that have been reflected or diffracted on their journey from the satellite to the receiver.
Precise+ is our new technology that extends the benefits of Supercorrelation to carrier-phase measurements, the key to high-precision GNSS receivers. By applying similar techniques but focusing on leveraging the benefits in the tracking of the carrier signal, the sharp accuracy degradation that affects high-precision GNSS receivers in difficult environments is significantly reduced, and high-precision GNSS accuracy extends much further into cities, forests or anywhere where GNSS signals are obstructed.
Just like S-GNSS, Precise+ is easy to integrate. No additional data is required in the GNSS receiver, no changes are required in the system design. The software in the GNSS receiver is updated to take advantage of Supercorrelation, and the system accuracy, availability and reliability are all improved.
How does the accuracy of Precise+ compare with existing GNSS receivers in open-sky and obstructed environments?
The system accuracy for an existing high-precision GNSS receiver and a Precise+ receiver is the same in open-sky environments: these systems operate normally, producing reliable positions with accuracy better than 1m when the signals are not obscured.
The system accuracy for an existing standard-precision GNSS receiver and an S-GNSS receiver are also the same as each other in open-sky environments: these systems operate normally, producing accuracy of about 2m when the signals are not obscured.
When these receivers move into urban areas, the performance of all but Precise+ changes. Receivers without Supercorrelation suffer problems caused by the signal obscuration. Existing high-precision receivers can no longer produce carrier-phase positions and fall back to the same, degraded accuracy as existing standard-precision receivers. An S-GNSS receiver can mitigate the effects of signal obscuration so suffers a small accuracy degradation and continues to produce reliable positions. A Precise+ receiver can mitigate the effects of signal obscuration and continues to produce positions of better than 1m accuracy.
What are the benefits of Precise+ for OEMs looking to advance autonomy?
Autonomous and highly automated systems define the boundaries of their functionality by specifying exactly how, when and where the system is designed to operate. This is the operational design domain (ODD). These systems often rely on GNSS as a core localization input. When signals degrade in urban canyons or under tree cover, conventional receivers force the system to fall back to less accurate sources or disengage the automated function entirely.
At the system level, GNSS accuracy and availability affect not just lane-level positioning but also the confidence bounds that safety systems use to validate sensor fusion. A Precise+ receiver maintains sub-meter accuracy where a conventional high-precision receiver would fall back to code-phase-only positions of several meters or worse, keeping the GNSS contribution useful rather than a source of uncertainty for which the rest of the system must compensate.
The result is an expanded operational envelope for autonomous systems, pushing high-precision GNSS availability into urban and mixed-environment routes where it has historically been least reliable, and where robust localization is needed most.