[time]
2022-08-26T00:09:00+02:00

[track]
7

[team_name]
imec-WAVES

[team_institution]
imec-WAVES

[logolink]


[team_members]


[reference_person]
sander.coene@ugent.be

[reference_email]
sander.coene@ugent.be

[description_short]
An advanced ranging algorithm produces distance estimates for each CIR. 
The training data provides optimal ranging algorithm parameters and bias correction terms.
A ML correction model is trained with location estimates as well as other predictors, to make the ranges even more accurate. 
Per-anchor range tracking to remove outliers range detection. 
A particle filter uses the error distribution from the training data to perform likelihood estimation.
P75 2D distance is used to fine-tune performance on the TestingTrial data.
We aim for faster-than-real-time update rate.

[description_long_link]
https://drive.google.com/file/d/1a6qfwN6g8kOPCyfKpz_0a9mYZCxrgsBB/view?usp=sharing

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true

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