|
Abstract
|
|
|---|---|
| Nonparametric belief propagation (NBP) is one of the best-known methods for cooperative localization in sensor networks. It is capable to provide information about location estimation with appropriate uncertainty and to accommodate non-Gaussian distance measurement errors. However, the accuracy of NBP is questionable in loopy networks. In this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST) created by breadth first search (BFS) method. According to our simulation results, NBP-ST performs better than NBP in terms of accuracy, computational and communication cost in the networks with high connectivity (i.e., highly loopy networks). | |
|
International
|
Si |
|
Congress
|
IEEE 72nd Vehicular Technology Conference Fall (VTC 2010-Fall) |
|
|
960 |
|
Place
|
Ottawa, Canada |
|
Reviewers
|
Si |
|
ISBN/ISSN
|
978-1-4244-3573-9 |
|
|
10.1109/VETECF.2010.5594105 |
|
Start Date
|
06/09/2010 |
|
End Date
|
09/09/2010 |
|
From page
|
1 |
|
To page
|
5 |
|
|
IEEE Proceedings of Vehicular Technology Conference Fall (VTC 2010-Fall) |