摘要： 针对室内WiFi和蓝牙单独定位时信标覆盖有限以及定位精度较低的问题,提出一种基于WiFi与蓝牙定位数据的优化贝叶斯融合定位算法。利用高斯核函数对WiFi及蓝牙单独定位结果处理后作为先验样本信息,通过秩和检验法分别计算出WiFi和蓝牙定位信息源的可信度,进行多源先验信息融合得到融合后的先验定位结果及分布,使用优化贝叶斯的后验分布密度函数估计出坐标偏差用以修正融合定位结果,得到WiFi和蓝牙融合定位坐标的最优估计值。实验结果表明,该算法可有效提高WiFi和蓝牙协同定位精度,在高斯噪声标准差为3 dBm的环境下,定位误差小于1 m的概率可达到95%,定位性能明显优于WiFi和蓝牙单独定位算法。

关键词: WiFi技术, 蓝牙, 贝叶斯估计, 高斯核函数, 可信度

Abstract: Aiming at the problem that the beacon coverage is limited and the positioning accuracy is low when the indoor WiFi and Bluetooth are located separately,an optimal Bayesian fusion and localization algorithm based on WiFi and Bluetooth positioning data is proposed.The algorithm first uses the Gauss kernel function to deal with the separate positioning results of WiFi and Bluetooth as a priori sample information.The rank sum test is used to calculate the credibility of the information source of WiFi and Bluetooth.Then the results and the distribution of the fusion results are obtained by the fusion of multi-source prior information.Finally,the optimal estimation of WiFi and Bluetooth fusion positioning coordinates is obtained by optimizing the distribution density function of the Bayesian and estimating the coordinate deviation.Experimental results show that this algorithm can effectively improve the cooperative positioning accuracy of WiFi and Bluetooth.Under the condition of Gauss noise standard deviation of 3 dBm,the probability of positioning error less than 1 meter can reach 95%.The positioning performance is obviously superior to that of the separate WiFi and Bluetooth localization algorithm.

Key words: WiFi, Bluetooth, Bayes estimation, Gauss kernel function, credibility

中图分类号: 

• TP391