基于不同邻近标签数选择的LANDMARC定位算法研究 |
投稿时间:2017-08-16 点此下载全文 |
引用本文:谢亚琴,王超.基于不同邻近标签数选择的LANDMARC定位算法研究[J].南京信息工程大学学报,2019,11(5):621~624 |
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基金项目:东南大学移动通信国家重点实验室开放研究基金(2012D20) |
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中文摘要:对于基于射频识别的LANDMARC室内定位算法而言,该系统采用"k近邻"算法,通过选取k个与待测标签相邻且符合特定条件的参考标签,最后根据这些标签的位置结合权值估算出待测标签的坐标信息.但是在实际的操作过程中,最近邻参考标签数的选取无指导原则,具有一定的盲目性.针对这一问题,通过选取与待定位参考点最近邻的参考节点作为未知点,通过搜索法获得最优的邻近标签数k,在随后的未知节点的定位过程中,选取k个邻近标签进行定位.经过多次实验,最终得出结论,使用改进后的LANDMARC算法的性能要优于原来经典的LANDMARC算法,精确度提升了10%左右,同时避免了k值选取的盲目性. |
中文关键词:邻近标签 LANDMARC 算法 室内定位 射频识别 |
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An improved LANDMARC method based on different neighbor reference nodes |
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Abstract:For radio frequency identification using the LANDMARC indoor positioning system,k-nearest neighbor reference tags that meet certain conditionswere selected,and the final position of the unknown tag was estimated according to those reference tags.However,the methods of selecting of the number of adjacent reference tags are also blindness.To solve this problem,the reference tag thatis nearest the unknown node is selected as an unknown point; then,the optimal number k is obtained by searching all feasible k values.Simulation results demonstrate that the performance of the improved LANDMARC algorithm is better than the traditional LANDMARC algorithm,and the accuracy improved by approximately 10%. |
keywords:neighbor reference nodes LANDMARC algorithm indoor positioning radio frequency identification |
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