Analytical Framework for Soft and Hard Data Fusion: A Dempster- Shafer Belief Theoretic Approach.

摘要

The recent experiences of asymmetric urban military operations have highlighted the pressing need for incorporation of soft data, such as informant statements, into the fusion process. Soft data are fundamentally different from hard data (generated by physics-based sensors), in the sense that the information they provide tends to be qualitative and subject to interpretation. These characteristics pose a major obstacle to using existing multi-sensor data fusion frameworks, which are quite well established for hard data. Given the critical and sensitive nature of intended applications soft/hard data fusion requires a framework that allows for convenient representation of various data uncertainties common in soft/hard data, and provides fusion techniques that are robust, mathematically justifiable, and yet effective. This would allow an analyst to make decisions with a better understanding of the associated uncertainties as well as the fusion mechanism itself.