{"title":"Quality of Service based Resource Management for Rotating Phased Array Radar","authors":"Jingbei Yang, Yuanli Feng, Junpeng Yu","doi":"10.1109/EEI59236.2023.10212593","DOIUrl":null,"url":null,"abstract":"The quality of service based resource management model (Q-RAM) provides a significant method for the resource management of multifunction radar (MFR), however, which is insufficient for the application in a rotating phased array radar (RPAR) because of the mechanical rotation of the antenna. In this paper, we present an extension of the Q-RAM resource management framework for RPAR. Our method includes task modeling, objective function building and constraints analysis, which are integrated as an optimized resource management method called Q-RRAM. This method combines Q-RAM with optimized utility functions for RPAR on each time step. More task types are considered to meet the practical application of radar. Simulation experiments are carried out and the results demonstrate that, comparing to the classical Q-RAM and rule-based method, our approach has better performance in the application of RPAR resource management.","PeriodicalId":363603,"journal":{"name":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 5th International Conference on Electronic Engineering and Informatics (EEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEI59236.2023.10212593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The quality of service based resource management model (Q-RAM) provides a significant method for the resource management of multifunction radar (MFR), however, which is insufficient for the application in a rotating phased array radar (RPAR) because of the mechanical rotation of the antenna. In this paper, we present an extension of the Q-RAM resource management framework for RPAR. Our method includes task modeling, objective function building and constraints analysis, which are integrated as an optimized resource management method called Q-RRAM. This method combines Q-RAM with optimized utility functions for RPAR on each time step. More task types are considered to meet the practical application of radar. Simulation experiments are carried out and the results demonstrate that, comparing to the classical Q-RAM and rule-based method, our approach has better performance in the application of RPAR resource management.