Multi-objective resource optimization simulation of multifunctional phased array radar

In response to the shortage of time resources for traditional multifunctional phased array radar to perform multitasking, a multi-target tracking algorithm based on fusion measurement and a comprehensive strategy adaptive resource scheduling algorithm are proposed. The performance of these two algorithms in handling multitasking is verified through simulation experiments. This experimental platform integrates functions such as radar resource scheduling, signal processing, and data processing to evaluate the performance and resource scheduling efficiency of multifunctional phased array radar for target detection and tracking in multitasking environments. The results indicate that the proposed multi-target tracking algorithm based on fusion measurement can optimize the performance of the radar system and improve the accuracy of target signal detection and tracking within limited time resources. Compared to traditional resource scheduling algorithms, the comprehensive strategy adaptive resource scheduling algorithm can allocate system resources more reasonably in the context of multitasking scheduling, significantly improving the resource utilization efficiency of multifunctional phased array radar.