|
Abstract
|
|
|---|---|
| Nonparametric belief propagation (NBP) is the well-known method for cooperative localization in wireless 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. Therefore, in this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST) created by breadth first search (BFS) method. In addition, we propose a reliable indoor model based on obtained received-signal-strength (RSS) measurements in our lab. According to our experimental results, NBP-ST performs better than NBP in terms of accuracy and communication cost in the networks with high connectivity (i.e., highly loopy networks). | |
|
International
|
Si |
|
Congress
|
International Conference on Sensor Technologies and Applications |
|
|
960 |
|
Place
|
|
|
Reviewers
|
Si |
|
ISBN/ISSN
|
978-1-4244-7538-4 |
|
|
10.1109/SENSORCOMM.2010.44 |
|
Start Date
|
18/07/2010 |
|
End Date
|
25/07/2010 |
|
From page
|
238 |
|
To page
|
243 |
|
|
IEEE proceedings of International Conference on Sensor Technologies and Applications |