Task scheduling algorithm based on value optimisation for anti‐missile phased array radar. Issue 11 (1st November 2019)

• Record Type: Journal Article
• Authors: Yang, Shanchao; Tian, Kangsheng; Liu, Renzheng
• Is Part Of: IET radar, sonar & navigation. Volume 13:Issue 11(2019)
• Page Start: 1883
• Page End: 1889
• Publication Date: 2019-11-01
• Subjects: missiles -- phased array radar -- genetic algorithms -- scheduling -- optimisation; task scheduling algorithm -- anti‐missile -- array radar -- ballistic missile targets -- task comprehensive priority -- two‐dimensional priority table -- target threat degree -- task deadline -- dynamic value function -- fixed value -- desired execution time -- value optimisation model -- genetic algorithm -- scheduling model -- scheduling timeliness -- traditional scheduling algorithms -- task value function -- scheduling performance -- traditional algorithms -- value achieving ratio; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2019.0163
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : 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.