Multi-Censor Fusion using Observation Merging with Central Level Architecture
Dil Muhammad Akbar Hussain, Zaki Ahmed, M. Z. Khan, Andrea Valente · University of Southern Denmark Research Portal (University of Southern Denmark) · 2011
Abstract—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.