Weighted positioning method based on RSSI probability distribution and Bayesian estimation
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摘要:
针对传统的基于测距的Wi-Fi定位技术未考虑接收的信号强度指示(RSSI)值的分布特性而造成室内定位效果欠佳的问题，提出了一种基于RSSI概率分布与贝叶斯估计的加权定位方法. 该方法在研究RSSI的平稳性、分布特性的基础上，通过贝叶斯估计将先验的RSSI概率分布引入权重的计算，给异常值较低的权重，降低了环境噪声和外界不确定因素对定位精度的影响，并以权重最大的位置作为定位结果. 实验结果表明：文中方法与三边定位、加权质心定位、权重校正的加权质心算法相比平均定位误差分别降低了45.4%、14.6%、8.2%，累积概率分布在50%内的误差分别降低了66.7%、42.1%、32.4%.
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关键词:
- 接收信号强度指示(RSSI) /
- Wi-Fi室内定位 /
- 概率分布 /
- 贝叶斯估计 /
- 高斯拟合
Abstract:Aiming at the problem that the traditional Wi-Fi positioning technology based on distance measurement does not consider the distribution characteristics of received signal strength indication (RSSI) values, which may result in poor indoor positioning results, this paper proposes a weighted positioning method based on RSSI probability distribution and Bayesian estimation. On the basis of studying the stationarity and distribution characteristics of RSSI. The method introduces the prior RSSI probability distribution into to the calculation of weight through Bayesian estimation. It can also give lower weights to outliers go as to reduce the impact of environmental noise and external uncertain factors on the positioning accuracy, then the position with the largest weight will be taken as the positioning result. Experimental results show that compared with results of trilateral localization, weighted centroid localization and weight correction algorithm, the average error of this method is reduced by 45.4%, 14.6%, 8.2%, and the error of cumulative probability within 50% is reduced by 66.7%, 42.1%, 32.4%.
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