14.6. Sources of GNSS Errors

• Imperfect satellite clocks cause small time errors, leading to position errors.

Satellite clocks are critical for GNSS accuracy. If a satellite's clock is not perfectly synchronized, it can show that a signal was sent at a different time than it actually was. This causes the GNSS receiver to miscalculate the distance to that satellite, which, in turn, affects the overall position accuracy. Even a small error in time can result in significant positioning inaccuracies on the ground.

Imagine a runner timing themselves with a stopwatch that is running 5 seconds late. Even if the runner runs a perfect lap, the stopwatch will show a time that is 5 seconds longer than the actual time. Similarly, if a satellite’s clock is slow or fast, the position calculated will not be accurate.

• Signals slow down in atmospheric layers, introducing delays.

GNSS signals pass through different layers of the atmosphere—primarily the ionosphere and the troposphere. The ionosphere, which is charged particles in the upper atmosphere, can cause delays due to variations in electron density. Similarly, the troposphere, which consists of water vapor and other gases, can also slow down signals. As a result, when signals are delayed, the GNSS receiver can misinterpret the time it took for the signal to arrive, leading to inaccuracies in positioning.

Consider how your voice sounds different when you speak underwater versus on land. Water and air both slow down sound waves but in different ways, leading to distortions. Likewise, the atmosphere affects GNSS signals, causing them to take longer to reach their destination.

• Signal reflections from surfaces like buildings or water bodies create errors.

Multipath effects occur when signals bounce off surfaces before they reach the receiver. For example, if a signal reflects off a large building or a body of water, it can arrive at the receiver later than expected. This can result in calculating an incorrect position since the receiver may think the signal came directly from the satellite without accounting for the reflection delay.

Think of an echo in a canyon: when you shout, the sound reflects off the canyon walls and reaches your ears later than the direct sound. Similarly, if GNSS signals bounce off tall buildings, this reflection can lead to erroneous positioning.

• Internal noise from the receiver’s electronics can distort measurements.

GNSS receivers convert signals into usable data. Internal electronics can introduce noise—a sort of random variability in measurements—that distorts the accuracy of the signals received from satellites. This noise can stem from various factors, like temperature variations or electronic interference, leading to less reliable positioning.

Imagine trying to listen to a radio station with static noise. You may hear the music, but the static distorts the sound, making it hard to understand the lyrics. Similarly, noise in GNSS receivers can obscure the accurate signals they receive, making the positions less reliable.

• Imperfect satellite ephemeris data leads to inaccuracies.

Ephemeris data provides information about a satellite's orbit. If this data is inaccurate or outdated, the GNSS receiver may calculate positions incorrectly. Since the satellites are constantly moving, even small inaccuracies in their predicted location can lead to significant positioning errors on Earth.

Think of it as trying to hit a target with a bow and arrow while being given inaccurate wind signals. If you aim based on past wind patterns that are no longer relevant, your arrow might miss the target entirely. Similarly, outdated orbital information can lead to inaccurate GNSS results.

• Poor geometry (satellites clustered together) increases Dilution of Precision (DOP).

The arrangement of satellites overhead affects positioning accuracy—a concept known as the geometry of the satellite constellation. If satellites are too close together in the sky, the receiver may struggle to pinpoint an exact location, leading to high Dilution of Precision (DOP). Ideally, satellites should be well-distributed for maximum accuracy.

Imagine trying to pinpoint your location in a city where you can only see a few close buildings. This might not allow you to determine your exact position in relation to the entire city. However, if you can see buildings spread across the skyline, you can estimate your location more accurately. Similarly, a well-distributed satellite geometry helps sharpen GNSS accuracy.

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