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Bayesian Algorithms for Indoor Radio Localization

Academic Article
Publication Date:
2007
abstract:
Localization of moving users or terminals (MTs) is one of the hottest topics in mobile radio/network research and development. User localization may be achieved by satellites (e.g., using the GPS or the forthcoming GALILEO satellite system) or radio. While in the first case one or more additional devices must be embedded in the user terminal, thus making it more complex and expensive, the latter scenario requires no additional devices since only radio/network services are employed. Radio-assisted localization is the only method suitable in indoor or urban canyon scenarios where satellite signals are not available.
Iris type:
01.01 Articolo in rivista
Keywords:
Bayesian methods; wireless localization; Hidden Markov Model; radio localization
List of contributors:
Rampa, Vittorio
Handle:
https://iris.cnr.it/handle/20.500.14243/435310
Published in:
ERCIM NEWS
Journal
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URL

http://ercim-news.ercim.eu/bayesian-algorithms-for-indoor-radio-localization
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