Name
Abstract | ||
|---|---|---|
In an ultra-wide band (UWB) sensor network signal reflections from objects can be used to accurately determine the location. UWB signals are preferred in these types of sensor networks since they provide a very good resolution due to their fine time granularity. We propose an artificial neural network based localization algorithm to detect single object in a sensor network and compare its performance to Cramer-Rao bound and least squares estimator. Then we propose a two phase algorithm for multiple object detection and evaluate the algorithm for the case when there are two objects in a sensor network with three nodes. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICC.2008.456 | Beijing |
Keywords | Field | DocType |
mobile computing,mobility management (mobile radio),neural nets,ultra wideband communication,wireless sensor networks,Cramer-Rao bound,TDOA,UWB sensor network,artificial neural network,least squares estimator,localization algorithm,multiple object detection,neural networks,single object detection,ultrawide band sensor network signal reflections | Cramér–Rao bound,Object detection,Computer science,Visual sensor network,Computer network,Brooks–Iyengar algorithm,Mobile wireless sensor network,Multilateration,Artificial neural network,Wireless sensor network | Conference |
ISSN | ISBN | Citations |
1550-3607 | 978-1-4244-2075-9 | 5 |
PageRank | References | Authors |
0.59 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Salih Ergüt | 1 | 365 | 19.17 |
| Ramesh R. Rao | 2 | 5 | 0.59 |
| Özgür Dural | 3 | 10 | 2.85 |
| Zafer Sahinoglu | 4 | 456 | 38.93 |