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Multitarget operations of UAV have high requirements for the route. The planning of the route is easily affected by the security, concealment and distance of the mission. There are many problems such as strong subjectivity, complex algorithm and different weight class. In order to overcome the shortcomings of traditional weight based evaluation functions, such as inconsistent dimension, strong subjectivity and uncontrollable progress, it is necessary to enhance the combat effectiveness of UAV on the ground and enhance operational effectiveness. The idea of Pareto optimal solution is adopted. Using fast non dominated sorting algorithm, taking track length, concealment and safety as specific evaluation indicators, we studied the path planning problem of multi-target mission optimization using NSGA- II algorithm, and verified it by simulation. The obtained optimal Pareto solutions generally reach a better level, and the different Pareto solutions have their own advantages. These advantages are adapted to different task needs respectively. This method has good flexibility and adaptability in unmanned aerial vehicle route planning.