As published in IoT Now, our CEO Scott Pomerantz, explains the impact of location accuracy on our everyday lives, and how a software upgrade with our Supercorrelation technology™ can solve the biggest problem in GPS.

What is the problem with the accuracy of our GPS?

Much of our economy is dependent on an incredible global navigation positioning and timing system (GNSS), with GPS being the most famous of the 4 GNSS systems.

Services like Google Maps and Uber have become part of our everyday lives, our transport and logistics systems are built on it, finance and banking rely on GNSS for security and authentication. But the worrying fact is that the accuracy and sensitivity of GNSS receivers is limited by the way that they currently process satellite signals – a situation that will only get worse as cities become more built up, and economies demand more from location-based services.

This causes every GNSS device from in-car sat navs, to smartphones, to wearables to suffer from inaccuracies. It’s the reason that the ‘blue dot’ on Google Maps can sometimes be in the wrong place and why your Uber driver sometimes can’t find you.

Historical benefits explained

GNSS is one of the marvels of the modern world. In 2021, the market was valued at 150.5 billion euros, with $1.4 trillion benefiting U.S. private sector industries since it was made available in the 1980s.

Most of this in just the last 10 years, through the explosive growth of location-based services offered through smartphones, watches and automotive vehicles.

The world’s most significant navigation problem

Despite its remarkable capabilities, GNSS does face certain limitations, with one of the most significant challenges being multipath interference. Multipath interference occurs when satellite signals reflect off buildings, trees, or other obstacles before reaching the receiver. These reflected signals can cause inaccuracies in positioning and timing measurements, degrading the overall performance of GNSS.

Multipath explained

Multipath interference can lead to errors in determining the user’s position, especially in urban environments or areas with dense vegetation. The reflected signals can arrive at the receiver slightly later than the direct signals, causing a discrepancy that affects the accuracy of the position calculation.

The economic cost of multipath interference to industry

The cost of multipath interference can be substantial, particularly in industries heavily reliant on GNSS for their operations.

In the transportation sector errors in vehicle positioning not only pose safety concerns but can also result in inefficient routing and increased fuel consumption. The economic consequences extend to logistics companies needing to optimize fleet management and delivery routes with inaccuracy leading to delays, increased fuel costs, and reduced operational efficiency.

Similarly, industries such as agriculture and construction heavily rely on GNSS for precision guidance and mapping applications. Errors in positioning can result in inaccurate data collection, leading to suboptimal decision-making in resource allocation, crop management, and construction site planning. These inefficiencies can have significant economic repercussions, impacting yields, project timelines, and overall profitability.

Even worse, the same vulnerability can be exploited by criminals and malicious actors by broadcasting fake signals known as spoofing, which can trick and mislead GNSS receivers.

When is good, good enough?

As our devices become more powerful, so too is the demand for higher levels of accuracy, reliability and security in location services. I believe that we have reached a tipping point where the demands of end users and the businesses that serve them are being held back by the performance of current GNSS receivers.

Automotive and autonomy

One immediate example is the demand for better advanced driver assistance systems (ADAS) and advanced navigation solutions including 3D mapping. As manufacturers roll out hands-free driving on freeways, so the demand grows for similar capabilities in urban areas. Consistently accurate positioning to a lane level is a key requirement for advancing ADAS solutions so they can work safely and reliably in cities. With current GNSS systems suffering from the problem of multipath, leading to inaccuracy and a consequent lack of confidence on our roads, manufacturers are beginning to demand a higher performance spec from GNSS receivers to enable both the safety and broad accessibility of autonomy.

Strengthening the integrity of GNSS

Our world is becoming more reliant on GNSS: by 2026 there are predicted to be 7.5bn mobile devices users worldwide. In order to achieve the levels of accuracy, reliability and security required for 21st century users, an update is required to the way in which GNSS receivers work.

The answer lies in upgrading the way that GNSS receivers interpret satellite signals – a simple but seismic change for this foundational technology.

This is achievable through our Supercorrelation™ software that can be embedded in standard receivers. Using machine learning algorithms and advanced physics, the performance can be boosted on smartphones, wearables and vehicles – making them more accurate and reliable, and more resilient to spoofing attacks.