Operator Use of Multi-Sensor Data Fusion for Airborne Picture Compilation

A study was conducted to examine the operational use of multi-sensor data fusion for military airborne intelligence, surveillance and reconnaissance. Participants performed a simulated picture compilation task wherein they had to identify all ships and planes in their area of operation using various sensors. One group performed the task using only native sensor data. The second group had imperfect data fusion to help them resolve the kinematic information, but they still had to identify each contact. The results indicated that data fusion automation improved the identification of ships and planes over the native sensor group. However, over time, map clutter continually increased for the group with fusion automation, surpassing the clutter for the native sensor group. The results suggest that while multi-sensor data fusion has benefits for picture compilation, dealing with plot clutter from false and spurious tracks is a key concern. Interface suggestions are provided to mitigate the effects.