postuloca:bayesian
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The figures in the following show the mass probability density of the localizzation error, when the bayesian approach is used. This method is described in the pape Savazzi & all; “Radio Imaging by Cooperative Wireless Network: Localizzation Algorithms and Experiments”; IEEE Int. Conf. WCNC 2012.
Scenario C40
In the following table, the VRTI dist. Error is the locallization error misured by the only Maximum Variance Image estimation,instead, Kalman dist. Error is the locallization error misured supporting the VRTI algorithm by the Kalman filter. Noise and No-Noise are the localization errors measured changing the parameters to calculate the weights of the regularization matrix.
| Scenario | Parameters | Anchor positions | VRTI error dist. Noise/No-Noise . | KALMAN error dist. Noise/No-Noise | Metrics VRTI / KALMAN | Notes and video |
|---|---|---|---|---|---|---|
| C 40 | area: 6.4 X 4.5 [m] anchors: 25 speed: 0.5[step/s] channels: 1 origin: WnLab |  |  |  | RMSE: 1.595 [m] / 1.588 [m] 75th pc: 1.946 [m] / 1.933 [m] 90th pc: 2.668 [m] / 2.624 [m] | Error with noise model in [0.8, 1] m. c40_25sen_1p_1sec.avi |
postuloca/bayesian.1364300428.txt.gz · Last modified: 2013-03-26 12:20 by pietro