李桢, 黄劲松. 基于RSSI抗差滤波的WiFi定位[J]. 武汉大学学报 ( 信息科学版), 2016, 41(3): 361-366. DOI: 10.13203/j.whugis20130801
引用本文: 李桢, 黄劲松. 基于RSSI抗差滤波的WiFi定位[J]. 武汉大学学报 ( 信息科学版), 2016, 41(3): 361-366. DOI: 10.13203/j.whugis20130801
LI Zhen, HUANG Jingsong. WiFi Positioning Using Robust Filtering with RSSI[J]. Geomatics and Information Science of Wuhan University, 2016, 41(3): 361-366. DOI: 10.13203/j.whugis20130801
Citation: LI Zhen, HUANG Jingsong. WiFi Positioning Using Robust Filtering with RSSI[J]. Geomatics and Information Science of Wuhan University, 2016, 41(3): 361-366. DOI: 10.13203/j.whugis20130801

基于RSSI抗差滤波的WiFi定位

WiFi Positioning Using Robust Filtering with RSSI

  • 摘要: 基于WiFi的定位技术中,对接收信号强度(received signal strength indication, RSSI)的平稳性要求较高,本文在分析室内WiFi信号强度统计特征的前提下,以Friis传输方程和运动学方程为基础,利用抗差卡尔曼滤波方法估计信号强度,达到了信号平滑的目的,从源头上为WiFi定位精度提供保障,定位结果表明采用本文所提方法可以明显提高定位精度。

     

    Abstract: In WiFi-based indoor positioning technology, the stability of the RSSI (Received Signal Strength Indication)is very critical. Based on analyzing the statistical characteristics of WiFi signal strength, the truth that the RSSI does not obey the normal distribution is proved, which provides instructions for the construction of stochastic model of filtering. By integrating Friis transmission equation and the kinematic equation into robust kalman filter method, we can reach the target of smoothing the signal, which can ensure the accuracy of WiFi indoor positioning from the signal source. According to the research results, the average positioning error in static applications can be reduced to 0.3 meters compare with the signal attenuation model, while for dynamic applications, it has a much better performance than the signal attenuation model, the average positioning error can be reduced from 5 meters to 1.4 meters.

     

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