Performance modeling for multisensor data fusion

With the evolution of computer and fusion algorithms, data fusion systems have been applied to many areas, both in civilian and military fields. In the past, in the multisensor fusion community, the research goal has been primarily focused on establishing a computational approach for fusion processing and algorithms. However, it will be very useful to be able to characterize the relationship between sensed information inputs available to the fusion system and the quality of fused information output. This will not only help us understand the fusion system performance but also provide high level performance bounds given sensor mix and quality for system control such as sensor resource allocation and estimate information requirements. This paper presents a fusion performance model (FPM) for a general multisensor fusion system. The model includes both kinematics and classification component and focuses on the two performance measures: positional error and classification error. The performance model is based on the Bayesian theory and a combination of simulation and analytical approaches. Simulation results that validate the analytical performance predictions are also included.