How I'm just wondering if somebody can explain about how can we get the CDF error for indoor localization as in example I found this quote in one of the paper
"Usually, the cumulative probability functions (CDF) of the distance error is used for measuring the precision of a system. When two positioning techniques are compared, if their accuracies are the same, we prefer the system with the CDF graph, which reaches high probability values faster, because its distance error is concentrated in small values. In practice, CDF is described by the percentile format. For example, one system has a location precision of 90% within 2.3 m (the CDF of distance error of 2.3 m is 0.9), and 95% within 3.5 m; another one has a precision of 50% within 2.3 m and 95% within 3.3 m. We could choose the former system because of its higher precision." I just didn't get it, can somebody help me to represent it with Maths plz
This quote is somewhat poorly worded but the way I read it was. For the first system, the reported location 2.3 meters or less away from the true location 90% of the time. Also for the first system the reported location is 3.5 meters or less away from the true location 95% of time. For the second system, the reported location is 2.3 meters or less away 50% of the time. Also for the second system, the reported location is 3.3 meters or less away 95% of the time. Precision usually means how close your results are to each other. If the results were Gaussian distributed, system 1 would be a Gaussian with a smaller variance and hence higher precision.