Least Square Localization Method Based on Anchor Nodes Optimization Selection
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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.

    Reference
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    附中文参考文献:
    [4] 闫雷兵,陆音,张业荣.基于改进最小二乘算法的TDOA/AOA定位方法.电波科学学报,2016,31(2):394-400
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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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  • Received:May 15,2017
  • Online: December 15,2017
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