Random finite set theoretic based soft/hard data fusion with application for target tracking

This paper reports on ongoing research on development of data fusion systems capable of processing soft as well as hard data. Such fusion systems are distinguished from the conventional systems where input data are assumed to be provided by typically well-characterized electronic sensor systems. The incorporation of soft human-generated data into fusion process is an emerging trend in fusion community majorly motivated by asymmetric warfare situations where observational opportunities for traditional hard sensors is restricted. Random finite set theory is a mathematical framework with powerful representational and computational abilities making it a promising approach to address several fundamental challenges in soft/hard fusion systems. In this paper the first prototype soft/hard fusion system based on random finite set theory is described. Experimental results obtained using the developed system prove the plausibility as well as efficiency of a random finite set theoretic approach to fusion of soft/hard data.