Bayesian approach to multisensor data fusion
Charles R. Smith · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
Multisensor data fusion is concerned with the integration and extraction of information from data obtained from two or more sources. Assuming the data are contaminated with noise, we present the necessary definitions and concepts to formulate multisensor data fusion as a problem of inference; specifically, we show in general and in a simple example how to assign probabilities for hypotheses expressed as propositions when data from two sources supply information relevant to the hypotheses. The example is concerned with target identification with a pulsed radar and a continuous-wave radar.