The path to mass market high precision positioning: Page 3 of 6

November 20, 2018 //By Thomas Nigg, u-blox
The path to mass market high precision positioning
If we’re going to see fully autonomous vehicles on our roads, a number of technologies need to hit maturity and then be rolled out simultaneously. Key among them is high precision positioning capability that’s reliable, affordable and scalable.

Delivering mass market high precision positioning using correction services

There are two approaches when it comes to delivering GNSS correction services. The first is observation space representation (OSR). Here, the service calculates the expected error at the location of each specific rover, and sends this directly to the rover device.

The other technique is called state space representation (SSR). Here, GNSS signal errors are monitored and then used to physically model errors spanning a full region, in a so-called ‘state space’ model. The data describing the model at a given point in time is transmitted to rovers right across the coverage area.

Only SSR can feasibly be scaled up to become a truly mass market solution. Here’s why.

Figure 1: How OSR and SSR work – and an at-a-glance comparison.

Applicable in situations needing centimeter- or millimeter-level accuracy, OSR is used in real time kinematic (RTK) and network RTK satellite navigation. OSR-based systems need a two-way link between the rover and correction data service provider. Moreover, for optimal accuracy, the rover must remain within 30 km of the base station. The challenge with OSR is that if it were to be adopted by the mass market, current mobile communication networks would struggle to reliably deliver the levels of communication required. Consequently, OSR isn’t ideally suited to mass adoption.

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