RECURSIVE TEMPORAL-SPATIAL INFORMATION FUSION WITH APPLICATIONS TO TARGET IDENTIFICATION

In this paper, centralized/distributed recursive algorithms for tempor al-spatial information integration using the Dempster-Shafer technique are developed. Compared with the Bayesian approach, the Dempster-Shaf er technique has the strong capability of handling information uncerta inties which is especially desired in many applications. In the centra lized integration algorithm, all information is pooled into the centra l processor and integrated. In contrast, the distributed integration a lgorithm shares the computational burden among the local processors, w hich increases the computational efficiency The developed algorithms a re effectively applied to a target identification problem with three s ensors: identification of friend-foe-neutral (IFFN), electronic suppor t measurement (ESM), and infrared search and track (IRST).