Achieving efficient mission performance of multi-function radars is a challenge because of resource limitations; thus, in this study, we examine a specific radar resource management technique. Previous studies have optimizing a single cost function to improve radar performance; however, other cost functions that include trade-offs must also be optimized. In this study, the relevant task is first vectorized, and the mission selection vector searches for the task to be performed. Then, using the Pareto optimal point, a tracking period that satisfies both dual cost functions of the task is found. The scheduling is finally performed by updating the new start time of the task for the corresponding tracking period. Simulation results show that it is possible to improve the radar cost value while minimizing the loss of the cost function using a trade-off relationship for optimizing the dual cost function.
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