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Satellite navigation is playing an increasing role in autonomous vehicles.
Satellite navigation is playing an increasing role in autonomous vehicles.
( Source: gemeinfrei / Pexels)

SATELLITE NAVIGATION Satellite navigation in autonomous vehicles

Author / Editor: Jamie Thomson / Isabell Page

A Global Navigation Satellite System (GNSS) is a group of artificial satellites that provide position data from their orbits. GNSS systems are being used in the development of autonomous vehicles to calculate latitude, longitude, speed and location to help navigate cars.

According to the European Global Navigation Satellite Systems Agency (GSA), the global GNSS downstream market is set to reach €150 billion with the technology having a significant impact on the road transportation and automotive sectors.

How satellite navigation is being used in connected cars

GNSS is being used to improve the efficiency of smart mobility applications. Primarily, it’s being used to provide connected vehicles with semi-autonomous navigation, alerting drivers when to turn through portable navigation devices (PNDs) and in-vehicle systems (IVS).

The technology is being used in fleet management to provide positioning information through telematics to enable transport operators to monitor logistics activities. GNSS also uses car location data to feed into satellite road traffic monitoring services that control the flow of traffic in urban areas.

Satellite navigation is an important feature in connected vehicle safety. For example, Europe’s eCall system uses GNSS to provide location information to emergency services, which speeds up driver assistance after road accidents. It’s used in insurance telematics, where good driving habits are recorded and rewarded with lower insurance premiums. GNSS is also used by police authorities to track the location of vehicles at different points during the day.

How GNSS works in self-driving cars

n self-driving cars, GNSS is used alongside LiDAR scanners to create extensive visual map databases that are combined with cameras, radars and lidars on the vehicle. The data gathered by the vehicle is processed by artificial intelligence (AI) algorithms that enable the car to steer on its own. Pattern recognition technology in the vehicle enables it to “read” street signs, recognise roads and register its position on the map.

Satellite navigation is proving to be a cost-effective way of monitoring a vehicle’s position in real time and with the integration of receivers and sensors, vehicles can still operate when satellite signals are intermittently unavailable.

The Massachusetts Institute of Technology (MIT) is currently developing a system that can drive autonomous vehicles using only GPS maps and video camera feeds. Their system uses machine learning to observe how a human driver steers in real life conditions and then trains the technology to learn all the directions. Here’s an overview of how MIT’s system works:

Another company advancing the use of GNSS in autonomous vehicles is Oxbotica. Their Selenium technology works independently of external infrastructures to allow vehicles to operate even without a GPS signal.

The challenges of using GNSS in self-driving vehicles

Two of the biggest challenges of using satellite navigation in autonomous vehicles are overcoming ‘jamming’ and ‘spoofing’. Jamming refers to the intentional interference of a signal, where electromagnetic fields are directed at GNSS frequencies to ‘jam’ them so they can’t be tracked by receivers. 

Whereas jamming causes a signal to die, spoofing causes a signal to lie. Spoofing creates a fake signal from a ground station that fools a satellite receiver into thinking that a vehicle is in a position that it’s not.

Both jamming and spoofing make autonomous vehicles vulnerable to security threats. For example, both interferences can be used to misreport a car’s location so it can be stolen. Likewise, because GNSS uses an open, unencrypted format, monetary transactions like those used in car sharing schemes can be intercepted for fraudulent activity.

To ensure the security of autonomous vehicles moving forward, satellite navigation systems in cars need to have strong, reliable, encrypted signals with associated technology that’s affordable for mass market application. One solution is STL (Satellite Time and Location), a source carried on the Iridium constellation of satellites. This purpose-built signal is 30 dB stronger than GNSS and offers encryption for protection against interference.

The future of satellite navigation in autonomous vehicles

As GNSS continues to be used in the development of self-driving vehicles, it will come to play an increasingly important role in the navigation of assisted driving. It will add to the safety of autonomous driving through its uses in telematics and congestion easing. It will also play a role in intelligent speed adaptation, instructing a vehicle to speed up and slow down.

In connected cars, GNSS is already being used in place of nomadic devices like portable receivers. Its increasing interoperability with other automotive technologies will start to see it converge with both sensor-based and connection-based approaches. In turn, this will reduce infrastructure costs, enabling a single, integrated system to provide positioning, navigation and timing functions for self-driving vehicles.

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