物联网中基于扩展卡尔曼滤波的移动群体定位

Extended Kalman Filter for Mobile Groups Users Localization in Internet of Things

为了满足高精度和高可靠性定位的需求,提出了一种基于扩展卡尔曼滤波的移动群体定位算法,把待定位的用户节点当成一个群组,利用他们之间的距离信息得到更好的定位性能,以减小环境噪声和无线信号不稳定造成的影响.此外,开发出一个实际的系统,并在大学校园里进行了大量实验.实验结果和理论分析验证了所提出方法的有效性.

In order to meet the requirement of high localization accuracy and the high reliable localization in some scenarios,the user nodes to be located were taken as a group to get better localization performance by utilizing the mutual distance information among them.A mobile group localization method was designed based on extended Kalman filter,which can alleviate the influence caused by environmental noisy and unstable wireless signals.Besides,a real system was implemented and experiments were performed on the campus of University.The experimental evaluations prove that the performance of the proposed method can effectively improve the localization accuracy.