Multi-Censor Fusion using Observation Merging with Central Level Architecture

Publication: Research - peer-reviewArticle in proceeding

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The use of multiple sensors typically requires the fusion of data from different type of sensors. The combined use of such a data has the potential to give an efficient, high quality and reliable estimation. Input data from different sensors allows the introduction of target attributes (target type, size) into the association logic. This requires a more general association logic, in which both the physical position parameters and the target attributes can be used simultaneously. Although, the data fusion from a number of sensors could provide better and reliable estimation but abundance of information is to be handled. Therefore, more extensive computer resources are needed for such a system. The parallel processing technique could be an alternative for such a system. The main objective of this research is to provide a real time task allocation strategy for data processing using multiple processing units for same type of multiple
sensors, typically radar in our case.
Original languageEnglish
TitleProceedings of the International MultiConference on Engineers and Computer Scientists, IMECS 2011
EditorsS. I. Ao, Oscar Castillo, Craig Douglas, David Dagan Feng, Jeong-A Lee
Number of pages4
VolumeVolume II
Place of publicationHong Kong
PublisherNewswood Limited, International Association of Engineers, IAENG
Publication date16 Mar 2011
Pages787-790
ISBN (print)978-988-19251-2-1
StatePublished

Conference

ConferenceInternational MultiConference on Engineers and Computer Scientists 2011
LandChina
ByHong Kong
Periode16-03-1118-03-11

Keywords

  • Target Tracking , Data Fusion, Sensor level, Parallel Processing

ID: 54872328