The objective of sensor fusion is to synergistically combine different sources of sensory information into one representational format to provide more complete and precise interpretation of the system. A generic sensor fusion framework based on a highly autonomous sensor (HAS) model is presented. The framework provides freedom to choose different data fusion methods and combine them together to achieve better performance. In the context of HAS's, this paper describes a hierarchical decentralized sensor-fusion approach based on a qualitative theory to interpret measurements, and on qualitative procedures to reason and make decisions based on the measurement interpretations. In this manner, heuristic fusion methods are applied at a high-qualitative level as well as at a numerical level when necessary. This approach implements intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors.