| 引用本文: | 焉晓贞,罗清华,马衍秀,周鹏太,杨一鹏,张辉,宋佳,王翥.锚节点优化选择的最小二乘定位方法.软件学报,2017,28(s1):39-49 |
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| 锚节点优化选择的最小二乘定位方法 |
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焉晓贞1,2, 罗清华1,2, 马衍秀2, 周鹏太2, 杨一鹏2, 张辉2, 宋佳2, 王翥2
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1.卫星导航系统和装备技术国家重点实验室(中国电子科技集团公司 第54研究所), 河北 石家庄 050081;2.哈尔滨工业大学(威海)信息与电气工程学院, 山东 威海 264209
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| 摘要: |
| 在最小二乘定位过程中，由于环境噪声、无线信号的多径、反射和非视距传输等复杂传输环境，以及距离估计过程中存在的缺陷等负面因素，引起在未知节点与各个锚节点间的距离估计结果中存在不同程度的误差，导致最小二乘定位精度较低.基于此，提出了基于最小标准差的锚节点优化选择的最小二乘定位方法（least square localization method based on anchor nodes optimization selection through minimum standard deviation，简称LS-ANOS）.首先，采用基于nanoLOC的双边对等测距方法多次重复测量未知节点到各个锚节点间的距离，并对这些距离估计值进行统计计算.然后，从输入测量误差对定位结果的影响机理出发，采用动态滑动窗口单遍扫描的策略，优化选择出高质量的距离估计值，从而确定优选的锚节点.最后，基于最小二乘定位计算实现了高精度的定位，为后续导航等应用处理方法提供先验和决策信息.实验及评估结果表明，基于最小标准差的锚节点优化选择的最小二乘定位方法能够有效地提高定位精度. |
| 关键词: 无线定位 最小二乘 质量评估 优化选择 标准差 |
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| 基金项目:国家自然科学基金（61671174，61601142）；卫星导航系统和装备技术国家重点实验室开放课题（EX166840037，EX166840044）；山东省自然科学基金（ZR2015FM027，ZR2014FM023）；航天科学技术基金（2017-HT-HG-16）；广西省重点实验室开放基金（YQ14205，YQ15203）；哈尔滨工业大学创新基金（HIT.NSRIF.2015122，HIT.NSRIF.201721）；威海市科技计划（16）；哈尔滨工业大学（威海）学科引导基金（WH20150211） |
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| Least Square Localization Method Based on Anchor Nodes Optimization Selection |
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YAN Xiao-Zhen1,2, LUO Qing-Hua1,2, MA Yan-Xiu2, ZHOU Peng-Tai2, YANG Yi-Peng2, ZHANG Hui2, SONG Jia2, WANG Zhu2
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1.State Key Laboratory of Satellite Navigation System and Equipment Technology(The 54 th Research Institute of China Electronic Science and Technology Group Inc), Shijiazhuang 050081, China;2.School of Information and Electrical Engineering, Harbin Institute Technology at Weihai, Weihai 264209, China
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| Abstract: |
| During the process of Least Square localization, some negative factors may give rise to different levels of noise, such as the environmental noise, the reflection, refraction, multipath and non-line-of sight (NLOS) complex propa gation of wireless signal, and the limitation of distance estimation method. And they also lead to low localization accuracy of Least Square localization. For this problem, this paper proposes an improved Least Square localization method, which is called Least Square localization based on anchor nodes optimization selection through minimum standard deviation (LS-ANOS). In LS-ANOS method, nanoLOC-based Symmetric Double Sided Two Way Ranging (SDS-TWR) is utilized to conduct distance estimation repeatedly between unknown nodes and anchor nodes. And statistical computation is performed on these distance estimation results. Then, from the influential mechenism of input measurement noise on localization result, the paper adopts slide window-based single scanning strategy to optimize the selection of the distance estimation result with higher quality and the corresponding anchor nodes. Lastly, based on the least square localization computation, it gets the accurate localization result. Simulation and experimental results demonstrate that the proposed method could improve the accuracy of Least Square localization method effectively. |
| Key words: wireless localization least square quality evaluation optimization selection standard deviation |
