{"title":"中段目标跟踪传感器管理算法研究","authors":"Bo Wang, W. An, Yiyu Zhou","doi":"10.1109/IWISA.2009.5073082","DOIUrl":null,"url":null,"abstract":"In allusion to sensor management problem of continual midcourse object tracking in the space tracking and surveillance system, a novel optimized objective function was proposed according to analysis of its restriction. Furthermore, on the basis of analyzing the disadvantages of binary particle swarm optimization based sensor management, a novel method based on real-number particle swarm optimization was proposed through dimensionality reduction and position vector improvement. Ultimately, simulation about classical midcourse object tracking scenario was executed, and the performance of several methods were compared in detail. The simulation results indicated that the novel optimized objective function could schedule sensors effectively; moreover, the proposed sensor management was a more efficient method.","PeriodicalId":6327,"journal":{"name":"2009 International Workshop on Intelligent Systems and Applications","volume":"18 1 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Sensor Management Algorithm of Midcourse Object Tracking\",\"authors\":\"Bo Wang, W. An, Yiyu Zhou\",\"doi\":\"10.1109/IWISA.2009.5073082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In allusion to sensor management problem of continual midcourse object tracking in the space tracking and surveillance system, a novel optimized objective function was proposed according to analysis of its restriction. Furthermore, on the basis of analyzing the disadvantages of binary particle swarm optimization based sensor management, a novel method based on real-number particle swarm optimization was proposed through dimensionality reduction and position vector improvement. Ultimately, simulation about classical midcourse object tracking scenario was executed, and the performance of several methods were compared in detail. The simulation results indicated that the novel optimized objective function could schedule sensors effectively; moreover, the proposed sensor management was a more efficient method.\",\"PeriodicalId\":6327,\"journal\":{\"name\":\"2009 International Workshop on Intelligent Systems and Applications\",\"volume\":\"18 1 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWISA.2009.5073082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2009.5073082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Sensor Management Algorithm of Midcourse Object Tracking
In allusion to sensor management problem of continual midcourse object tracking in the space tracking and surveillance system, a novel optimized objective function was proposed according to analysis of its restriction. Furthermore, on the basis of analyzing the disadvantages of binary particle swarm optimization based sensor management, a novel method based on real-number particle swarm optimization was proposed through dimensionality reduction and position vector improvement. Ultimately, simulation about classical midcourse object tracking scenario was executed, and the performance of several methods were compared in detail. The simulation results indicated that the novel optimized objective function could schedule sensors effectively; moreover, the proposed sensor management was a more efficient method.