On Bayesian tracking and data fusion: A tutorial introduction with examples

This tutorial paper provides a short introduction to selected aspects of sensor data fusion by discussing characteristic examples. We consider three cases when fusion of sensor data is important: when emphasis is placed on data produced at different instants of time (i.e., target tracking), when data being collected from different sensor sources are important, and when we have data with background information on the sensor performance as well as data with nonsensor context information. The feedback from data processing to the data acquisition process is illustrated by a sensor management example.