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| 基于秩滤波和裴波那契树的信号强度定位算法 | |
| 引用本文： | 余修武,肖人榕,刘永,郭倩,余昊. 基于秩滤波和裴波那契树的信号强度定位算法[J]. 北京邮电大学学报, 2019, 42(2): 7-12. DOI: 10.13190/j.jbupt.2018-120 |
| 作者姓名： | 余修武 肖人榕 刘永 郭倩 余昊 |
| 作者单位： | 南华大学资源环境与安全工程学院,湖南衡阳421001;铀矿冶放射性控制技术湖南省工程研究中心,湖南衡阳421001;湖南省铀尾矿库退役治理工程技术研究中心,湖南衡阳421001;南华大学资源环境与安全工程学院,湖南衡阳,421001 |
| 基金项目： | 国家自然科学基金项目（11705084）；湖南省重点研发计划项目（2018SK2055）；国家应急管理部安全生产重特大事故防治关键技术科技项目（hunan-0001-2018AQ）；铀矿冶放射性控制技术湖南省工程研究中心、湖南省铀尾矿库退役治理技术工程技术研究中心联合开放课题重点项目（2018YKZX1009） |
| 摘 要： | 针对接收信号强度指示（RSSI）测距定位精度和鲁棒性差的问题，提出了一种基于秩滤波和裴波那契树的信号强度定位（RF-RSSI-FTO）算法.采用秩滤波方法对RSSI值进行去干扰滤波处理，可提高测距精度及鲁棒性；引入裴波那契树优化算法对定位坐标进行全局和局部搜索寻优处理，可减小定位误差.仿真结果表明，RF-RSSI-FTO算法能有效改善测距精度和鲁棒性，增强全局和局部搜索能力，提高定位精度. |
| 关 键 词： | 无线传感器网络 接收的信号强度指示 秩滤波 鲁棒性 裴波那契树 |
| 收稿时间： | 2018-06-27 |
Signal Strength Localization Algorithm Based on Rank Filter and Fibonacci Tree |
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| YU Xiu-wu,XIAO Ren-rong,LIU Yong,GUO Qian,YU Hao. Signal Strength Localization Algorithm Based on Rank Filter and Fibonacci Tree[J]. Journal of Beijing University of Posts and Telecommunications, 2019, 42(2): 7-12. DOI: 10.13190/j.jbupt.2018-120 | |
| Authors: | YU Xiu-wu XIAO Ren-rong LIU Yong GUO Qian YU Hao |
| Affiliation: | 1. School of Resource and Environment and Safety Engineering, University of South China, Hunan Hengyang 421001, China; 2. Hunan Province Engineering Technology Research Center of Uranium Tailings Treatment, Hunan Hengyang 421001, China; 3. Hunan Province Engineering Research Center of Radioactive Control Technology in Uranium Mining and Metallurgy, Hunan Hengyang 421001, China |
| Abstract: | In order to solve the problem of poor ranging accuracy and robustness of received signal strength indication (RSSI), a signal strength localization algorithm based on rank filter and Fibonacci tree optimization (RF-RSSI-FTO) was proposed. First, the rank filtering method was used to remove the interference of the RSSI value to improve the accuracy and robustness of the ranging. Then, the Fibonacci tree optimization algorithm was introduced to optimize the global and local search of the positioning coordinates to reduce the positioning error. Simulation results show that the RF-RSSI-FTO algorithm can effectively improve ranging accuracy and robustness, enhance the global and local search ability, and improve positioning accuracy. |
| Keywords: | wireless sensor network received signal strength indication rank filter robustness Fibonacci tree |
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