Whether accuracy depends on the location update rate splits into several questions and answers. There are even seemingly contradictions. But there are no contradictions – just different usage scenarios.
Key topics to understand:
Let’s first consider NIA as an example. It is the easiest-to-understand architecture:
Thus, the biggest misconception of linking between location update rate and accuracy is the following:
“If you have a 1Hz location update rate or 10Hz location update, will the accuracy be higher in the 10Hz, because the object is moving and while it is moving, its location is changing? Therefore, if it changes, we cannot measure it precisely if our location update rate is slow, right?”
No, it is not a correct assumption because:
Imagine that we don’t care about latency and care only about the location update rate. It is possible to gather several location updates, interpolate them, and populate with as many intermediate location measurement points, thus, effectively having as high a location update rate as you wish.
For example, this is precisely what the Realtime Player in the Dashboard does:
Reducing latency for ultrasound-based systems is difficult because of the slow speed of ultrasound wave propagation. The very reason ultrasound-based location systems are so precise is the core reason it is challenging to have low latency. Let’s calculate:
The statement that by tolerating the higher latency is possible to get higher accuracy seemingly contradicts the earlier given statement that the accuracy doesn’t depend on the location update rate. Both are correct.
We have a train of location updates. We can get higher accuracy if we accumulate several of them and perform all sorts of mathematical operations. It is very straightforward for static and slow-moving objects, but with not too complex logic, it can also be shown for fast-moving objects.
For static and slow-moving objects: for N samples and N-time increase in latency, it is possible to achieve sqrt(N) time accuracy improvement just by averaging. Thus, of 16-time averaging, it is possible to reduce the noise of the location measurement by a factor of 4.
See below an example of the Realtime Player (RTP) affecting the resulting noise of the location measurement that drops significantly when the RTP is activated. But for the expense of latency.