Sensor task priorities are the important foundation for sensors management. In this contribution a fuzzy management scheme is proposed to cope with the evaluation of multi-sensor task priorities in air surveillance applications. Based on all fused track and identified data, a fuzzy neural network determines the priority of each surveillance task to perform during the decision cycle. The structure of the fuzzy neural network is constructed first, the linguistic variables and terminology are defined, and the nodes function and the learning rules of the fuzzy neural network are designed then, finally a sensor task priorities evaluation example is given to demonstrate the validity of the fuzzy neural network evaluation approach in the sensor management application. Included results illustrate how the importance of the tasks, measured through their time-varying priorities, allows timely adapt sensor operation to changing situations.