• 论文
主办单位:煤炭科学研究总院有限公司、中国煤炭学会学术期刊工作委员会
基于TOA压缩感知的矿井分布式目标定位方法
  • Title

    Mine distributed target location method based on TOA compressed sensing

  • 作者

    刘真真田子建王文清徐志明刘婷黄蕾张向阳

  • Author

    LIU Zhenzhen,TIAN Zijian , WANG Wenqing ,XU Zhiming,LIU Ting,HUANG Lei,ZHANG Xiangyang

  • 单位

    中国矿业大学(北京)机电与信息工程学院北京工业职业技术学院

  • Organization
    1.School of mechanical and electrical information engineering China University of Mining and Technology(Beijing),Beijing ,China; 2.Beijing Polytechnic College,Beijing , China
  • 摘要

    基于目前矿井集中式目标定位系统存在可靠性较差的问题,分析构建分布式矿井目标定位系统的必要性以及优势,并提出分布式矿井目标定位系统的组成框架。为实现分布式矿井定位计算机低功耗、轻量化,提出基于指纹库压缩感知的矿井分布式目标定位方法,介绍基于指纹库压缩感知矿井分布式目标定位方法的离线和在线定位2个阶段的主要工作流程,进行了粗定位过程和精定位过程的算法设计,实现了仿真验证方案的设计和算法编程。研究结果表明:基于TOA压缩感知的矿井分布式目标定位方法在定位误差和实时性有较好的性能,其定位误差与网格划分的数量有关系,相同的巷道定位区域情况下网格数量越大,其定位误差越小。

  • Abstract
    Based on the problem of poor reliability of centralized target positioning system, the necessity and advantages of constructing distributed target positioning system were analyzed.The composition framework of distributed target positioning system was proposed.In order to realize the low power consumption and weight saving of distributed mine positioning computer, a distributed mine target localization method based on fingerprint database compression perception was proposed.The main work chart of offline and on-line positioning based on the fingerprint sensing compressed sensing mine distributed target localization method was put forward.The algorithm of coarse positioning process and fine positioning process were designed.The simulation verification scheme design and algorithm programming were realized.Simulation results showed that the method proposed in this paper had good performance in positioning error and real-time performance.The positioning error was related to the number of grids.The larger the number of grids was, the smaller the positioning error was in the same laneway locating area.
  • 关键词

    矿井定位分布式目标定位指纹库压缩感知

  • KeyWords

    mine location; distributed; target location; fingerprint database; compressed sensing

  • 基金项目(Foundation)
    国家重点研发计划专项资助项目(2016YFC0801800);国家自然基金资助项目(51674269);北京工业职业技术学院重点课题资助项目(bgzykyz201605,bgzyky201780z);
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主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会

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