Data models

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Several sources of error make raw GPS measurements inaccurate. To make up for this, consumer GPS receivers use a "model" to help determine what part of the measurement is error. Basically, the model tells the receiver what kind of motion it can expect. If a measurement indicates motion that doesn't fit the model, then the receiver assumes it must be noise, and ignores it.

In many consumer GPS receivers, the model is presented as a choice between "car" and "pedestrian" modes. In the FlySight, a few more choices are available, and it's not too hard to guess what kind of motion each might assume:

Model Expected motion
Portable Unknown
Stationary No motion
Pedestrian Slow, mostly horizontal motion
Automotive Fast, mostly horizontal motion
Sea Entirely horizontal motion
Airborne 3D motion with limited acceleration

It's important to understand the role the model plays. For example, if you set the FlySight to use the "Pedestrian" model, and then you jump from a plane, it will try to reconcile your rapid descent with its idea of how a pedestrian moves.

Less obviously, if you tell the FlySight to use the "Airborne < 1G" model, and then you perform a maneuver which results in more than 1G acceleration, the FlySight will "overshoot", because it chalks some of that acceleration up to noise.

When flying a wingsuit, we recommend the "Airborne < 1G" model. For swoopers, we recommend the "Airborne < 2G" model", since high performance landings can generate more than 1G acceleration.