Recursive algorithms for information fusion using belief functionswith applications to target identification

摘要

Recursive centralized and distributed algorithms for fusingtemporal and spatial information are developed for joint and disjointmeasurement data structures using the belief function approach. Thealgorithms have strong capability for handling information uncertainty.The effectiveness of the algorithms is demonstrated by a targetidentification problem