Exploitation of a priori knowledge for information fusion E ´ loi Bosse ´ a,b, * , Pierre Valin c , Anne-Claire Boury-Brisset a , Dominic Grenier b a Defence R&D Canada Valcartier, 2459 Pie-XI Blvd North, Val-Be ´lair, QC, Canada G3J 1X5 b De ´pt. de Ge ´nie Electrique et Ge ´nie Informatique, Universite ´ Laval, QC, Canada G1K 7P4 c Lockheed Martin Canada, 6111 Royalmount Avenue, Montre ´al, QC, Canada H4P 1K6 Received 7 May 2004; received in revised form 2 November 2004; accepted 2 November 2004 Available online 13 December 2004 Abstract The Information Fusion (IF) process is becoming increasingly more sophisticated, particularly through the incorporation of methods for high-level reasoning when applied to the situation analysis domain. A fundamental component of the IF process is a database (or databases) containing a priori knowledge that lists expected objects, behaviors of objects, and relationships between objects as well as all the possible attributes that can be inferred from measurements coming from a given sensor suite. We first pres- ent the basic concept of an existing support database (consisting of more than 2200 platforms) for Identity information fusion, and discuss its extension for higher-level fusion (e.g. situation and threat assessment). The database contains all the salient features needed for refining the identity of any target by the fusion of sensor information, and for addressing the situation and threat posed by groups of objects. The database is especially well suited for use in a Dempster–Shafer evidential reasoning scheme although it can also be used with Bayesian reasoning, if a priori probability distributions are known. Convincing results on several realistic scenarios of Maritime Air Area Operations and Direct Fleet Support are presented. This paper then develops the advanced concept of a Knowledge Management and Exploitation Server (KNOWMES) to support the IF process, through the use of ontologies and het- erogeneous knowledge sources, which are necessary for higher level fusion. Ó 2004 Elsevier B.V. All rights reserved. Keywords: Platform database; Identity information fusion; Knowledge server 1. Introduction Situation Awareness (SAW), a state in the mind of a human, is essential for commanders to conduct decision- making (DM) activities. It is about the perception of the elements in the environment, the comprehension of their meaning, and the projection of their status in the near future [1]. Situation Analysis (SA) [2] is defined as a pro- cess, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e. a state of SAW for the decision maker. Data/informa- tion fusion is clearly a key enabler for SA. According to Steinberg et al. [3], in their revision of the model pro- posed by the JDL sub-panel, data fusion is the process of combining data to refine state estimates and predictions. The Information Fusion (IF) techniques being devel- oped to support SA are becoming increasingly more sophisticated, particularly through the incorporation of methods for high-level reasoning processes. A funda- mental component of these processes is a database (or databases) containing a priori knowledge that lists ex- pected objects, behaviors of objects, and relationships between objects. A priori knowledge contains static (or slowly chang- ing) information/knowledge to support the various pro- cesses providing the decision-maker a higher level of 1566-2535/$ - see front matter Ó 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.inffus.2004.11.001 * Corresponding author. Address: Defence R&D Canada Valcar- tier, 2459 Pie-XI Blvd North, Val-Be ´lair, QC, Canada G3J 1X5. Tel.: +1 418 8444000; fax: +1 418 8444538. E-mail address: eloibosse@yahoo.ca (E ´ . Bosse ´). www.elsevier.com/locate/inffus Information Fusion 7 (2006) 161–175