基于线性内插法改进的室内定位算法
发布时间：2018-10-20 12:22
【摘要】：针对室内位置指纹定位技术存在的离线阶段工作量大、定位精度有限、顽健性较差的缺点,提出了一种基于线性内插法改进的指纹定位匹配算法。与传统位置指纹定位技术相比,该算法不仅降低了整体工作量,而且降低了多径效应造成的不利影响。最后搭建实验场景对该算法定位性能进行测试。实验数据显示,该算法与WKNN法相比,平均定位精度大约提高了34.25%,绝大部分待测点的定位误差在0.4 m以内,验证了所提算法在定位精度、顽健性和适应环境变化方面的优势。
[Abstract]:Aiming at the disadvantages of indoor location fingerprint location technology, such as large workload in off-line stage, limited location accuracy and poor robustness, an improved fingerprint location matching algorithm based on linear interpolation is proposed. Compared with the traditional location fingerprint location technique, the algorithm not only reduces the overall workload, but also reduces the adverse effects caused by the multipath effect. Finally, the experiment scene is built to test the localization performance of the algorithm. Experimental data show that the average positioning accuracy of the proposed algorithm is about 34.25% higher than that of the WKNN method, and the positioning error of most of the points to be measured is less than 0.4 m, which verifies the advantages of the proposed algorithm in positioning accuracy, robustness and adaptation to environmental changes.
【作者单位】： 西安邮电大学;
【基金】：陕西省工业科技攻关项目(No.2014K05-09) 陕西省教育厅科学研究计划项目(No.14JK1660)~~
【分类号】：TN911.7
本文编号：2283168
[Abstract]:Aiming at the disadvantages of indoor location fingerprint location technology, such as large workload in off-line stage, limited location accuracy and poor robustness, an improved fingerprint location matching algorithm based on linear interpolation is proposed. Compared with the traditional location fingerprint location technique, the algorithm not only reduces the overall workload, but also reduces the adverse effects caused by the multipath effect. Finally, the experiment scene is built to test the localization performance of the algorithm. Experimental data show that the average positioning accuracy of the proposed algorithm is about 34.25% higher than that of the WKNN method, and the positioning error of most of the points to be measured is less than 0.4 m, which verifies the advantages of the proposed algorithm in positioning accuracy, robustness and adaptation to environmental changes.
【作者单位】： 西安邮电大学;
【基金】：陕西省工业科技攻关项目(No.2014K05-09) 陕西省教育厅科学研究计划项目(No.14JK1660)~~
【分类号】：TN911.7
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