Research Paper Summary - A General Data Fusion Architecture

H Carvalho, W Heinzelman, A Murphy, and C Coelho. A
general data fusion architecture. In Int. Conf. on Info. Fusion,
pages 1465–1472, 2003.


This is a short paper that describes an architecture for data fusion. What they are proposing is a taxonomy that defines 3 types of fusion: data oriented, variable oriented, and a mixture of the two. They are making a clear distinction between data as a measurement of the environment and variable as determined by feature extraction.

They describe examples of sensor data and state that the data needs to be pre-processed before fused. The pre-processing can involve conversions of a signal or filtering or handling noise. After pre-processing the data can be fused and they are proposing a 3-level data fusion framework. They begin by classifying the data as defined by the taxonomy. Basically when the fusion occurs defines what type of fusion we are dealing with (data, variable or mixture).

They go into a few examples of using this architecture. In general, the paper is not detailed enough to understand if the approach is viable. It is high level and short. It does provide additional information about the formalities of data fusion which is useful.