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基于TOA压缩感知的矿井分布式目标定位方法 被引量:4

Mine distributed target location method based on TOA compressed sensing
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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。 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.
作者 刘真真 田子建 王文清 徐志明 刘婷 黄蕾 张向阳 LIU Zhenzhen;TIAN Zijian;WANG Wenqing;XU Zhiming;LIU Ting;HUANG Lei;ZHANG Xiangyang(School of mechanical and electrical information engineering China University of Mining and Technology(Be~iing),Beijing 100083,China;Beijing Polytechnic College,Beifing 100042,China)
出处 《煤炭科学技术》 CAS 北大核心 2018年第9期188-195,共8页 Coal Science and Technology
基金 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)
关键词 矿井定位 分布式 目标定位 指纹库 压缩感知 mine location distributed target location fingerprint database compressed sensing
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