GPS is the most famous of the four global navigation satellite systems (GNSS) and one of the marvels of the modern world. A GNSS constellation consists of a number of satellites that circle the globe to provide worldwide position, time and velocity information. Since these are low power signals and won’t travel through solid objects, it is normally important to have a clear view of the sky to get an accurate location.

The GNSS annual market is now valued at over €150bn (£129bn) through the explosive growth of location-based services offered through smartphones, watches and automotive vehicles. Services like Google Maps, Waze and Uber have become part of our everyday lives and our transport, logistics and financial systems are highly dependent upon these services.

Despite its remarkable capabilities, GNSS does face certain limitations, with one of the most significant challenges being multipath interference. This occurs when satellite signals reflect off buildings, metalwork or other reflective objects before reaching the receiver in your smartphone, watch or automobiles. These reflected signals can cause significant inaccuracies in the measurements, which degrades the overall performance of a position calculation. Performance degrades significantly the more reflective objects that are in the environment in which you find yourself, typical of dense modern cities.

With couriers working daily in the hardest GNSS environments, it becomes almost impossible for companies to know exactly what’s happening as drivers are dispatched. Logistics businesses require systems that function seamlessly in all operational environments, so that end user customers receive the highest level of customer service.

Amazon alone ships 1.6m packages per day. Those parcels need to be delivered to the doors of customers, many of which live and work in modern dense urban jungles. Each driver is required to deliver between 250 and 300 packages a day to over 200 stops. Efficiency is absolutely key to success.

The cost of poor positioning can be substantial. Errors in positioning result in significant economic consequences from inefficient routing, increased fuel consumption, delays to delivery schedules and lower customer satisfaction.

Current GNSS receivers need to supply higher levels of accuracy, reliability and security across these critical industries and in all environments — suburban, urban and skyscraper jungles. This challenge can be solved by upgrading the way that GNSS receivers interpret satellite signals; a simple but seismic change for this foundational technology.

Using modern signal processing and machine learning techniques, the problem of multipath and spoofing can be solved, dramatically improving the performance for smartphones, wearables and vehicles in the deepest of urban environments.

Scott Pomerantz, CEO, FocalPoint