Task Scheduling Algorithm Based on Value Optimization for Anti-missile Phased Array Radar

A task scheduling algorithm based on value optimisation is proposed under comprehensive priority for anti-missile phased array radar. The model of threat degree is established for ballistic missile targets. The task comprehensive priority is obtained utilising a two-dimensional priority table which synthesises the target threat degree and the task deadline. Then, based on the comprehensive priority, each task gets a dynamic value function, instead of a fixed value as usual. In this way, the task value is enlarged when it is executed close to the desired execution time. A value optimisation model for task scheduling is constructed, and the genetic algorithm is utilised to solve this scheduling model. Thereby tasks can be executed as close as possible to the desired time, and the principle of scheduling timeliness can be better achieved. The performance of the proposed algorithm (PA) is compared with traditional scheduling algorithms by simulation experiments, as well as the impact that parameters of task value function have on scheduling performance is analysed. Simulation results show that compared to the traditional algorithms, the PA reduces the average time shift ratio and improves the value achieving ratio.