Title :
Intelligent Fusion and Asset Management Processor
Author :
Gonsalves, Paul G. ; Rinkus, Gerard J.
Author_Institution :
Charles River Anal., Cambridge, MA, USA
Abstract :
Owing to continual advances in sensor capabilities, avionics, and inter-service C4I, the volume of battlefield intelligence data to which the modern-day military intelligence analyst has access is increasing at an exponential rate. This has created the need for more intelligent systems capable of scanning and extracting the tactically most useful information for presentation to the human analyst. The presence of a more extensive and flexible sensor asset infrastructure also mandates more intelligent and accountable asset deployment and management. Accordingly, we describe an effort to develop for the Air Force Research Laboratory´s Information Directorate an Intelligent Fusion and Asset Management Processor (IFAMP) for enhancing tactical situation awareness and for providing needs-based sensor asset planning and scheduling information to assist the C2 staff. The IFAMP architecture incorporates three distinct modules: a fuzzy logic-based level one fusion module responsible for low-level event detection, unit/echelon type discrimination, observation-to-track gating and assignment, and track database management; a belief network-based level two situation assessment module responsible for generating probabilistic hypotheses for high-level situational state descriptors; and a fuzzy logic-based level four collection management expert system responsible for mapping informational requirements and current state information into asset resource requests
Keywords :
belief maintenance; data analysis; database management systems; expert systems; fuzzy logic; military computing; scheduling; sensor fusion; Air Force Research Laboratory; IFAMP; Intelligent Fusion and Asset Management Processor; avionics; battlefield intelligence data; belief network; database; event detection; expert system; fuzzy logic; military intelligence analyst; probabilistic hypothesis generation; scheduling; sensor; sensor asset planning; tactical situation awareness; Aerospace electronics; Asset management; Data mining; Fuzzy logic; Fuzzy systems; Humans; Hybrid intelligent systems; Intelligent sensors; Intelligent systems; Resource management;
Conference_Titel :
Information Technology Conference, 1998. IEEE
Conference_Location :
Syracuse, NY
Print_ISBN :
0-7803-9914-5
DOI :
10.1109/IT.1998.713519