Eduard Escalona is a Market Development Innovation Officer at the European GNSS Agency (GSA. He talks about the innovations of the GNSS constellations over the last decade and what that’s done for the receivers on the ground.
The European GNSS Agency was established in 2004 with its headquarters in Prague, Czech Republic.
GSA oversees the operational management of the European navigation satellites, EGNOS and Galileo. They also monitor the market and the related technology. They engage with the industry and users to raise awareness of the systems and increase adoption. They also support creating new and innovative applications supported by the navigation systems’ positioning.
Every two years, GSA produces a GNSS Market Report and a GNSS User Technology Report.
For the technology monitoring, we continuously observe the receivers and everything related to Global Navigation Satellite System ( GNSS) technology. Every year, we examine over 500 receiver models and their market penetration.
The bi-annual reports are based on the latest trends, new requirements and learning about the users of the technology.
Satellites are getting better, and the number of constellations is increasing. Still, many people are not using GNSS terminology — they call it GPS, which is the American GNSS.
There is Galileo (European), GLONASS (Russian), or BeiDou (Chinese). Back in 2000, there were 40 GNSS satellites. Fast forward to 2021, and we now have over 100.
To derive a position and to know where your receiver/device is located, you need the visibility of at least four satellites.
Three satellites to calculate the position, and another one to synchronize the receiver.
Satellites work by sending out signals, telling you where they are positioned. The receiver calculates the time that is traversing the signal to know the satellite’s distance. When you have more visibility of satellites, it’s much easier to derive your position with better accuracy.
More visibility of satellites ensures better availability and better continuity of the positioning. This is useful in urban canyons — in the middle of the city with tall buildings — where the visibility of satellites is more limited.
Previously, with only one constellation and GPS, you could see perhaps two or three satellites and quickly lose the positioning within the city. This is now rare to see in devices that support multi constellations. Plus, all the constellations are built to be compatible with each other — all the receivers that can see multiple constellations can compute the position using the different satellites.
The satellites broadcast signals which are captured by the receivers. These signals use specific standardized frequencies that travel in space. Traveling through the ionosphere, the atmosphere’s different layers, creates errors and delays. These translate to worse accuracy.
Not so long ago, we had 5-7 meters of accuracy with a single frequency. Today, with more frequencies, it’s relatively common to have dual frequency or even triple frequency in devices.
Every time a different frequency traverses into the atmosphere, it behaves differently. Even if frequencies are sent simultaneously, when they arrive at the receiver, they arrive at different times, which helps to compute the errors produced in the ionosphere. You can correct those errors at the receiver for better accuracy and robustness.
Multipaths are also problematic. The signal is bounced off the ground or buildings. You receive multiple copies of a signal (not a fake) that aren’t real signals from the satellites, and this complicates the position’s computation.
Using multi-frequency and new modernised signals helps reduce these multipath errors received at the receiver.
Having more frequencies makes the system more immune to interferences, with other systems working close to a specific frequency. When you have a choice of frequencies, you can ignore the one that’s being interfered with and use other ones.
Frequencies are decided at the pre-design stage, so it’s not possible to change the number of frequencies on an existing satellite. The lifespan of a satellite is around 10 years. They’re designed to be future proof so that new requirements and functionalities can be later accommodated.
Now that there is a massive increase in multi-constellation and multi-frequency, dual-frequency has become the standard de facto for smartphones. All the new smartphones support multi-frequency, and this is the real breakthrough.
Higher accuracy and better availability are available to not only high-end professional devices but also high volume devices.
There are three major categories.
One — high volume devices, such as smartphones. They’re mass-market or location-based systems in which they are characterized by lower consumption. They are used in emerging markets such as autonomous systems or drones, where those devices also support multi-constellation.
Even low-cost phones support several constellations, dual-frequency, and incorporate other types of sensors for movement.
Two — safety or reliability critical devices. These devices need integrity and robustness from the system and from the positioning, as they support a market constrained by regulations. Thus, in terms of GNSS technology, the evolution is not as substantial as for high-volume devices because of certifications and regulations and many layers of approvals. It’s lower in adoption.
Three — high accuracy devices. These are used in professional environments and require much higher performance than the ordinary positioning people need for a smartphone to locate someone on the street. For instance, surveying or precision agriculture needs down to millimeter accuracy. They have very stringent requirements for accuracy, availability, and convergence times, and these devices are more advanced and expensive.
To compute centimeter or decimeter accuracy, they also require external systems to correct the propagation errors through the ionosphere and other error sources. These are the most advanced devices, always up-to-date with innovation. As soon as there’s a new frequency or new constellation they support it. They are expensive and not made for everyone.
Smartphones went from being a device to make calls to something you can use to take photographs, count your steps, and many other things. It’s an almost professional device for certain things.
At the same time, we see the miniaturization of high accuracy devices. Take mapping or asset inventory — you can use your smartphone for some professional applications.
The line is blurring.
Still, certain limitations, like the antenna’s size to support different frequencies, will keep the mass market and the professional devices separate. Plus, the chipsets used in professional devices to support these frequencies are expensive, and there are professional features that the mass market simply doesn’t need.
There’s an example for Galileo of how this gap is closing. Users will be able to access GNSS’s raw measurements to complete corrections on their smartphones. The performance capability won’t be the same as in a professional device. Still, it will open up possibilities for receiving higher accuracy (down to decimeter) to smartphones and not only through professional devices.
This paves the way to the new independent professional called “Bring your own device.”
What does the user need? How can the service satisfy their needs?
They need availability, accuracy, security, and connectivity. They need future proof systems to support upcoming technologies, autonomous driving, robotics, or drones.
Availability is addressed by adding more constellations or more satellites.
For accuracy, there are correction services that were first written for professional segments and are now available to mass market devices — for example, for autonomous driving.
We are presently building a new service called the Galileo High Accuracy Service (HAS) to provide corrections directly from the satellites on a new frequency. The receiver will use those corrections to correct its positioning and reach decimetre accuracy.
These are significant breakthroughs. It shows how you can change the satellite to provide new services to adapt to this evolution by monitoring the market’s needs.
For security, we address the vulnerabilities of GNSS.
Jamming is a way to scramble your signal so you cannot receive it. You don’t know your location because you don’t receive the GNSS signal.Spoofing can be done easily with simple devices, and they can fake the signal of GNSS. You receive a fake signal telling you are somewhere else.
It happens often, and we’re soon implementing authentication systems. For Galileo, it’s called OS-NMA (Open Service Navigation Message Authentication). It’s a message authentication that sends you a signature message to reassure you that the GNSS signal you received came from Galileo and not another source.
The driver in all this is the evolution of requirements. The market drives the development of the receivers and the system itself. The market needs to be considered when upgrading the current satellites and designing the next generation of satellites coming out in 10 years.
Imagine you want to pay for something. Many payment systems check your location to authenticate the purchase. They need to make sure you’re not trying to fake your location and do stuff from somewhere other than where you are.
Payment companies need to know your exact location.
Or take agriculture. Farmers receive subsidies from the Common Agricultural Policy (EU). They need to show what crops they produce and give regular updates to prove. Farmers use images and positioning to show what they produce. The payment agency somehow needs to verify these images’ trueness and that the farmers are not submitting images of the neighbor’s farm.
Spoofing is on the rise because these systems are cheap and easy to set up. The GNSS signals weaken because they come from far. Spoofing devices are on the ground and produce a much stronger signal. Your receiver takes the strong signal instead of the true one.
Ensuring the signal you receive is original and from trustworthy sources is vital.
We need to go in that direction.
Cellular networks are also another type of ground-based systems. Location-based 5G networks are not just for telecommunications but also for indoor location. When you go inside a tunnel, you lose the reception of GNSS — it’s a known problem.
The overall positioning system takes the input from all the other essential sources. This way, you’ll not rely on a single positioning system, but on many — this provides more robustness and backup in case of spoofing, jamming, or a system failure.
A wide range of applications requires robustness, such as autonomous driving or other safety-critical applications where you cannot afford to lose the positioning if there is any autonomous system using the position as an input.
We’re heading for the hybridization of sensors and other ground systems together with GNSS, where the systems are entirely integrated and understand each other.
I think it would be risky.
Sure, there are other sensors to provide positioning. For example, with the advance of more powerful processing techniques, LIDAR systems could eventually become real-time.
Camera sensors can check the environment, and the location can be determined by comparing that to a 3D map. This is already possible.
But these are systems that locate you based on your relation to other objects. GNSS provides an absolute position. It’s reliable, and it’s been used for many years. With improvements, it continues to be dependable.
GNSS satellites are all around the world — wherever you travel, you have visibility of satellites, and you get a position. Suppose you travel by car and you cross a border. In that case, if the ground-based system is national, you have to rely on agreements between different national providers to provide a seamless transition of your position — similar to how it’s done in telecommunication. This can be overly complex.
GNSS is free and accessible. It’s global and dependable.
GNSS systems produce PNT (Position, Navigation, and Timing).
The satellites have precise clock systems. Many systems on Earth require accurate timing to synchronize networks and make the distribution. There are many use cases in which GNSS timing plays a significant role.
For telecoms, signals and systems need precise timing synchronizing. They require accurate clocks, which the satellites provide worldwide.
For energy, distribution also relies on an accurate and robust synchronization system. In finance, the stock exchange and other banking mechanisms need to be time-stamped accurately. A few seconds in time difference can mean millions for the stock exchange.
GNSS is an accurate source of timing and synchronization for these applications.
The High Accuracy Service for Galileo is happening. Other regional systems will also have some corrections distributed through the satellites, such as the Australian SBAS, which will work corrections directly through the satellites.
The Japanese QZSS also supports corrections by the satellites.
This democratizes high accuracy, and you’ll be able to come up with accuracies up to 20 centimeters on inexpensive devices. That opens up further applications and a vast range of innovations that right now we can’t even foresee — just think of robotics, drones, or autonomous driving.
For authentication, which no other system has yet, we currently rely on other ground infrastructure to do calculations. Once this functionality comes directly through the satellites, it’ll make things simple. Plus, it will open new markets because right now, some markets cannot rely on sources of positioning if they’re not entirely trustworthy. When you have the authentication put in place, it invites new markets to use GNSS systems.
What we see as the primary driver of increase in the usage of GNSS for the last two years are smaller devices. People don’t need high-end professional devices to benefit from the powerful GNSS receivers and high accuracy. These smaller devices are being put in high-volume applications, such as autonomous driving, together with other IT innovations.
More and more IoT devices support positioning. Cloud-based systems make compute capabilities more accessible from a wide variety of devices. The resulting data feeds machine learning algorithms, and with artificial intelligence, we’re heading to a more autonomous world.
Next five years?
More accurate positioning will make the world more digital and autonomous.
The number of constellations, not only GNSS, is increasing. Many satellites provide internet connectivity, like the LEO mega-constellations.
We need to know where they are at any given time. Satellites move in orbit, and there are deviations in the orbits. These are important for LEO satellites because there is a drag from the atmosphere pushing them down.
You need to correct these orbits, and you need a navigation satellite system to locate those satellites.
This is an area called Space Situational Awareness (SSA). We need to track all the objects in space, including satellites and debris.
I’d like to highlight a few ideas I found particularly interesting about this podcast episode.
The first one being that we need to prove our location — authenticate — that we’re connected to our GNSS satellite and proving that the location we see on our device is not being spoofed or altered.
Eduard touched upon the GNSS solution of, I guess, embedding a code in the signal and using that as verification that you were connected to an authoritative service like the GNSS satellite.
There are a couple of other different projects out there doing something similar. One is foam.space, and the other is xyo.network. Both provide a decentralized network and a way of proving your location built on the Internet of Things, only via two slightly different approaches.
Then, there’s securing documents by location — setting up a geofence. The documents cannot be visible outside of that location. When we have an accurate location available to us on our everyday devices, this will mean that we can do things like this.
A previous MapScaping podcast episode covered not documents but making sound available as certain geolocation. You could create a sightseeing tour of a city, lay a sound based on the location, and build up an experience that can only be experienced as you move through a scene, location, or area.
Then, there’re satellites using the GNSS platform to navigate their journey through space. ESRI made a map of all the stuff that’s orbiting our planet. You can click on “junk,” “non-junk,” big or small “satellites,” and look at different orbit times.
Esri mapped 18,000 of the 19,000 things — satellites, objects, pieces of junk — that are orbiting our planet at any given time.
It’s astounding how many things are orbiting our planet.
Be sure to subscribe to our podcast for weekly episodes that connect the geospatial community.
For more exclusive content, join our email. No spam! Just insightful content about the geospatial industry.
Geospatial standards, like any standard, are what we agree on as a community. It’s a way to describe how we model geospatial data, exchange it, subset it, process it, visualize it, or reference it. We need standards because we share and integrate data, and we solve complex problems.
Google Earth Engine is acloud computing platform for scientificanalysis andvisualization of geospatial data sets. It isfree to use for research, education, and nonprofit. Google Earth Engine is essentially streaming data. You don’t need to go online to download the data — you just need a browser, and you can access the entire Google Earth Engine data catalog and a bunch of tools to do the analysis and visualization.