Name
Abstract | ||
|---|---|---|
The problem of estimating the spatial distribution of radiation using measurements from a collection of spatially distributed sensors is considered. A parametric approach is adopted in which the field is modelled by a weighted sum of Gaussians, i.e., a Gaussian mixture. This is a valid approach for a large class of fields, e.g., absolutely integrable fields. Two Bayesian estimators based on progressive correction are proposed to estimate the mixture parameters. The first performs progressive correction using a Gaussian approximation while the second uses a Monte Carlo approximation. It is demonstrated that the Gaussian approximation is capable of accurate estimation using both simulated and real data. |
Year | Venue | Keywords |
|---|---|---|
2009 | FUSION: 2009 12TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4 | Radiological field estimation,Bayesian estimation |
DocType | Citations | PageRank |
Conference | 5 | 0.82 |
References | Authors | |
4 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark R. Morelande | 1 | 195 | 24.96 |
| Alex Skvortsov | 2 | 31 | 6.52 |