汪伦杰, 廖兴宇, 潘伟杰, 吕健. 基于信号均值滤波+k-means+WKNN的Wifi指纹定位算法研究[J]. 微电子学与计算机, 2017, 34(3): 30-34.
引用本文: 汪伦杰, 廖兴宇, 潘伟杰, 吕健. 基于信号均值滤波+k-means+WKNN的Wifi指纹定位算法研究[J]. 微电子学与计算机, 2017, 34(3): 30-34.
WANG Lun-Jie, LIAO Xing-Yu, PAN Wei-Jie, LV Jian. Wifi Fingerprint Location Algorithm in Indoor Location Based on Signal Mean Filter+k-means+WKNN[J]. Microelectronics & Computer, 2017, 34(3): 30-34.
Citation: WANG Lun-Jie, LIAO Xing-Yu, PAN Wei-Jie, LV Jian. Wifi Fingerprint Location Algorithm in Indoor Location Based on Signal Mean Filter+k-means+WKNN[J]. Microelectronics & Computer, 2017, 34(3): 30-34.

基于信号均值滤波+k-means+WKNN的Wifi指纹定位算法研究

Wifi Fingerprint Location Algorithm in Indoor Location Based on Signal Mean Filter+k-means+WKNN

  • 摘要: 首先利用平滑均值滤波方法对采集信号的RSSI值进行均值平滑处理, 提高信号采集的精度; 其次利用k-means聚类算法对指纹库进行优化提高指纹库的精度; 最后在KNN算法的基础上采用加权的方法来进行改进, 形成新的指纹算法WKNN, 并将新的指纹匹配算法WKNN应用到文本设计的Wifi指纹定位系统中.实验结果表明: 该改进算法在定位精度和稳定性方面较传统Wifi指纹定位算法有大幅度的提高.

     

    Abstract: In this paper, we first make use of the smoothing mean filtering method to smooth the RSSI value of the signal in order to improve the accuracy of signal acquisition.Secondly, we use k-means clustering algorithm to optimize the fingerprint database in order to improve the accuracy of the fingerprint database.Finally, we used a weighted approach to improve the traditional KNN algorithm and form a new fingerprint matching algorithm WKKN.The experimental results show that: Improved algorithm proposed in positioning accuracy and stability than traditional fingerprint Wifi positioning considered to have greatly improved.

     

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