Microsimulation as a tool for target tracking and state estimation
Donald E. Brown, Clarence Louis Pittard · 2002
Data fusion systems process large amounts of data into information for decision support. One of the fundamental components of data fusion is state estimation which provides estimates of current and future environmental states. Traditionally the state estimation procedures in data fusion have been accomplished by Kalman filtering techniques. However, these methods have difficulties with domains such as ground operations where past behavior does not correlate as highly with future behavior. This paper provides an overview to the use of microsimulations for state estimation in this domain.