ge and Carrier Wave Calculations
Up to now, we’ve described the calculations underlying GNSS as determining the distance between a satellite and a receiver. We know our position is somewhere in the range of this satellite, and by multiplying the signal’s travel time by the speed of light, we can measure an estimated distance from our receiver to the satellite. This simplified equation solves for what we call a “pseudorange” -- this distance is estimated because there could be errors in the position from atmospheric delays and other factors.
This equation is straightforward, but only gives meter-level accuracy. There’s another method using the carrier signal to significantly improve accuracy in high precision applications of GNSS.
The carrier phase calculation is a bit more complicated. Instead of solving distance based on the signal’s travel time, we’re solving for the number of wave cycles that occurred. A cycle is counted from one tip of a wave to the next. Remember that we know the frequency of the carrier signal so using that we can calculate the wavelength. By multiplying the carrier wavelength by the number of cycles that have occurred, we can compute a more accurate distance than when calculating only the pseudorange.
However, while we can now calculate positioning to a centimeter-level, counting the exact number of wave cycles between the satellite and the receiver is difficult. That means we need to verify this measurement with an additional computation. This process is called Ambiguity Resolution.
Both equations are used across GNSS applications because they are useful in different ways. While pseudorange measurements are less precise, they do not have a carrier phase ambiguity. This is what we mean when we say pseudorange measurements are accurate but not precise.
Conversely, carrier phase measurements are highly precise, but typically need additional infrastructure to resolve ambiguities. For this reason, the carrier phase is often used to calculate positioning in a specific region or area, like a farmer’s field.
Use of these measurements depends on your specific application, but I should add that NovAtel receivers are designed to process both calculations and are flexible across user applications.
Our next episode will describe the ways in which common errors are resolved through equipment, algorithms, and other technologies. But, if you’re ready to get a head start in learning these GNSS concepts, you can download our book An Introduction to GNSS on our website.
Hexagon | NovAtel Corrections Services Product Manager Jennifer Busser explores the methods used to reduce GNSS errors in episode four of our on-demand webinar series. From equipment to additional services, these methods help your solution deliver a position you can trust.
Hello, and welcome to episode four of Hexagon NovAtel’s webinar series on An Introduction to GNSS. My name is Jennifer Busser; I’m the correction services product manager at Hexagon’s Autonomy and Positioning division. Thanks for joining me! Today, we’re going to be exploring how to reduce GNSS positioning errors.
This episode explains some important techniques for reducing GNSS errors and improving position accuracy. I’ll share how your choice of GNSS equipment can impact position quality, and how your position can be improved further by GNSS correction data.
I recommend downloading our Introduction to GNSS book for a more in-depth look at reducing errors in GNSS systems.
Identifying GNSS Errors
As we saw in episode two, basic errors occur at all stages of GNSS positioning: clock and orbit errors are introduced at the satellite; the satellites’ signals are sped up or delayed as they move through the earth’s atmosphere; and as they get closer to the ground, they could reflect off buildings before finally getting to the antenna receiver.
With improvements in technology, scientists and engineers have developed a variety of methods to reduce these errors. Let’s dive into how we can make our positioning more reliable and accurate through our equipment, and correction services.
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