Sensor fusion is the combining of sensory data or data derived from disparate sources. By fusing sensor data from multiple sources in this way the resulting information can inform applications with far greater certainty than would be possible when consumed individually. Certainty in data can mean more accurate, more complete, or more dependable decisions are able to be formed.


The data sources for a fusion process are not specified to originate from identical sensors. One can distinguish direct fusion, indirect fusion and fusion of the outputs of the former two. Direct fusion is the fusion of sensor data from a set of heterogeneous or homogeneous sensors, soft sensors, and history values of sensor data, while indirect fusion uses information sources like a priori knowledge about the environment and human input.

Sensor fusion is also known as (multi-sensor) data fusion and is a subset of information fusion.