复杂室内环境下的WiFi定位技术研究

在复杂的室内WLAN环境下,利用改进的MK模型和加权K最近邻法对定位性能进行了改进。首先介绍了室内传播模型及改进的MK模型；然后介绍了位置指纹定位方法及两种定位算法的基本原理,根据实测数据,分析了以上方法的定位效果以及误差来源；最后提出了MK模型和加权K最近邻法相结合的混合定位法,并对算法进行了仿真和分析。仿真结果表明,所提算法提高了算法精确度,减小了定位误差。

Study on WiFi Location Technology under Complex Indoor Environment

Under the complex indoor wireless local area networks(WLAN) environment,the improved motley keenan(MK) model and the weighted K nearest neighbors(WKNN) positioning methods are used to improve the performance of location.Firstly,the indoor propagation models and the improved MK model are introduced.Then,the fingerprint positioning methods and the basic theories of those two positioning algorithms are illustrated.According to the experimental data,the positioning performance and error sources of those methods are analyzed.Finally,the combined hybrid positioning method between MK model and WKNN was proposed,and the simulation and analysis were made.Simulation results show that the proposed algorithm improves the accuracy and reduces the positioning error.